Syst. Res. 29, 342—367 (2012) Library Closure a… · Systems Research and Behavioral Science Syst. Res. 29, 342—367 (2012) Published online 24 February 2012 in Wiley Online Library

Systems Research and Behavioral ScienceSyst. Res. 29, 342—367 (2012)Published online 24 February 2012 in Wiley Online Library(wileyonlinelibrary.com) 001: 10.1 002/sres.21 11

• Research Paper

Operational Closure and Seif-Reference:On the Logic of Organizational Change

Markus Schwaninger1and Stefan N. Groesser2*1 Llniversity of St. Gallen, Institute of Management, St. Gallen, Szvitzerland2 Bern University ofApplied Sciences - School of Business, Bern, Switzerland

H The concept of autopoiesis introduced by Maturana and Varela has, in the last fourdecades, triggered intellectual efforts for the understanding of phenomena of seiforganization in general. This contribution aims at conceptualizing and applying two aspectsof autopoiesis—operational ciosure and sef-reference—in respect of social organizations. Weformalize these concepts and demonstrate their power to explain change processes. This isachieved by means of a qualitative case study and a quantitative simulation model, whichlead to counterintuitive insights about the dynamics of organizational transformation.Copyright © 2012 John Wiley & Sons, Ltd.

Keywords operational ciosure; seif-reference; autopoiesis; organizational change; organizationaltransformation; case study; formal model; simulation; System dynamics; mathematical modeling;bifurcation

INTRODUCTION

The introduction of the concept of autopoiesis intoscientific discourse (Varela et al., 1974) has triggered much discussion over the last decades. Ifautopoiesis, from the Greek roots autos (seif)and poie (to make), means self-production, it carries a conriotation of seif-organization, a conceptwhich has been at the core of the efforts of cyberneticians to reconstruct their science: first, to expand cybernetics from the domain ofmechanical systems to the realm of organismicsystems, and later, to the domain of human and

‘Correspondence to: Stefan N. Groesser, Bern University of AppliedSciences - School of Business, Bem, Switzerlancl.E-mail: [email protected]

social organizations. The cybemetics of mechanical systems and organisms was termed FirstOrder Cybernetics, and the cybernetics of humanand social systems Second-Order Cybernetics, alsocalled ‘the New Cybernetics‘. The difference wasessentially because of the introduction of theobserver: Heinz von Foerster (1984) labeled theformer ‘the cybernetics of observed systems‘and the latter ‘the cybernetics of observing systems‘. Whereas in the first case, the emphasisof description, explanation and design falls oninformation, feedback and adaptation, the newcybernetics has developed its own language,making use of concepts such as autopoiesis,self-organization, operational closure and selfreference. We return to these concepts shortly.

Receiveci 13 April 2011Accepted 31 January 2012Copyright © 2012 John Wiley & Sons, Ltd.

Syst. Res. RESEARCH PAPER

Ihis contribution is in the ambit of SecondOrder Cybemetics. Our aim is to conceptualizethe notions of operational ciosure and sef-referencefor organizational contexts. This endeavour isprimarily a theoretical one. Beyond that, we alsodemonstrate the relevance of our work for therealm of concrete social organizations. The existing literatitre treats the two concepts in such away that they remain difficult to grasp, that is,they are not presented in a compact, accessibleform. This motivates us to develop a parsimonious formulation of both concepts and to darify them in terms of organizational change. Ourresearch effort is stimulated by the followingquestions: What is the meaning of operationalciosure and seif-reference in organizationalcontexts? How can these concepts be expressedformally? Finafiv, are these concepts insightfuldescriptors of processes of organizational change?

We examine if and to what extent the conceptsof operational ciosure and seif-reference are heipful in illuminating phenomena of organizationalchange, concepts which may differ from mostestablished organizatiori theories1 by highlighting aspects, which existing theories cannot donceptualize. Why do we concentrate on thesetwo concepts and not others? The writings ofboth Humberto Maturana and Francisco Varela,including those co-authored by both men, revolvemainly around autopoiesis and operational closure. Other authors who have engaged in similardiscussions, as weh as having complemented andcontinued the work of Maturana and Varela, havealso included sef-organization and sef-reference. Weuse a synthetic approach, focusing on operationalclosure and self-reference as a pars pro toto, whichaccounts for all four concepts enumerated above.Such a synthesis is essential; it yields understanding (Ackoff, 1981: 17).

In the following section, the crucial conceptsare presented. Thereafter, we discuss these concepts in the context of the organizational domainand proceed to their formahization. Based on thatformulation, a qualitative case study is presentedas an exemplar to be built on in the rest ofthe paper. Thereafter, in the largest section, we

1 We are referring here to ‘mainstream‘ organization theories, as mostof the ones related in compendia such as Bullinger et eI. (2009).

Copyright © 2012 John Wiley & Sons, Ltd.

elaborate a Computer model, which expands onthe formulation developed earlier. By means ofsimulations, the general ideas of the paper areimplemented and used in the interpretation ofthe case study. The discussion of the simulationexperiments leads to insights, wbich are condensed in the conclusion.

CONCEPTS

With the concept of autopoiesis, Maturana andVarela ‘wanted a word that would by itself convey the central feature of the organization of theliving, which is autonomy‘ (1980: XVII). In theirseminal paper, they ‘claim that the notion ofautopoiesis is necessary and sufficient to characterizethe organization of living systems‘ (Maturana andVarela, 1980: 82). Reproduction and evolutionoccur in living systems, and the phenomenaderived from them ‘arise as secondary processessubordinated to their existence and operation asautopoietic unities‘ (1980: 112). System theoryhas viewed the concept of living Systems in different ways. In the work of Maturana and Varela,the notion of a living System 5 essentially confined to biological organisms. They do not claimthat their propositions concerning autopoiesiswould apply to the domain of social systems(Maturana and Varela, 1980).2 In General SystemTheor the notion of living systems pervades allkinds of systems, for example, Miller‘s (1978)scheine of living systems subsumes the System levelsfrom cell to organ, organism, group, organization,community, societ to supranational systems. Hecorroborates bis claim by identifying emiricallyan isomorphic structure of 20 subsystems, whichis applicable to each one of these levels. Milleruses terms such as ‘auto-regulation‘ (also ‘seif-regulation‘) and ‘self-organization‘ as relevant on alllevels of living systems (Miller, 1978: 346, 486)but does not deal with organizational ciosureor self-reference. In the wake of Maturana and

2 According to Varela, social systems are not autopoietic, but they areoperationally closed. Luhmann, 00 the other hand, conceptualizessocieties es autopoietic (Mingers, 1993: 211).

Nineteen subsystems are described in Miller (1978). The last subsys

tem. the hmer, is added bv his wife Jessie Miller at a later stege.

Syst. Res. 29, 342—367 (2012)DCI: 10.1002/sres

Operational Ciosure and SeIf-Reference 343

RESEARCH PAPER Syst. Res.

Varela, later authors, especially Luhmann, haveapplied the concepts of autopoiesis and operational ciosure to social Systems as weil (Jantsch,1980; Luhmann, 1995, 2003; Bailey, 1997).

Autopoiesis signifies the reproduction of the elements of a System by the System itseif or, moregenerally, the self-generation and self-productionof the system. The environment has no directinfluence on an autopoietic system, except itsdestruction. Therefore, autopoietic systems aredenoted as operationally closed. A system is considered a system only if it is operationally closed,that is, if the System produces and sustains itseifon the basis of its elementary Operations (Krause,2001: 121). An example of this is the brain of ahigher-order organism that is thermodynamically open but organizationally closed (Varelaet al., 1974). Hence, it is open for the exchangeof energy and information, but at the same time,it is operationally closed in the sense that its processes are self-activating and recursive and donot start or stop anywhere (Thompson et al.,2005: 44). Closure is about the circularity ofOperations producing Operations and must notbe confounded with closedness, which impliesisolation. An organisrn keeps all, or a certain part,of the relations between its elements invariant,despite perturbations, which stern from theorganism‘s internal dynamics as weil as from itsrelationships with other systems (Maturana andVarela, 2009: 180). Changes of the system aretriggered by internal structures and dynamics,not by changes in external factors. However, theperturbations (which include ‘interventions‘)coming from outside can trigger major changeindirectly and, therefore, necessarily only viaseif-reference. For instance, the rise of a newtechnology does not determine the reaction of acompany. That reaction is the result of processeswithin the organization, which rnay lead toadaptation. OnIy in the case of the destructionof a system is the impact direct.

Sef-reference ‘denotes a statement which refersto itseif or its own referent‘ (Bolander, 2009: 1).This definition stems from iinguistics. lt can be

For a critical discussion concerning the transfer of the concept ofautopoiesis to social Systems, see especially Mingers (1995, 2002) andKing and Thornhill (2003).


elevated to a more general level by claiming thatseif-reference denotes any act that refers to itseifor its own referent. In Computer science, forinstance, seif-reference is important to instantiatereflection, which enables a program to read orchange the instructions that govern it. Similarly,reflection is a basic capability of social Systems;it enables them to decipher, ponder, describe, criticize and change the rules that govern theirbehaviour. A respective analysis follows in thenext section.

OPERATIONAL CLOSURE AND SELFREFERENCE IN SOCIAL SYSTEMS

Let us first revert to operational closure in thecontext of social Organizations, a context whichcan be conceptualized in different ways. Many ofthe existing concepts of social organizations arefocused on the physical manifestations of thesesystems, for example, organizations as mechanisms or organizations as organisms (for details,see Morgan, 1997). Others constitute social systems as psychic or socio-psychic phenomena(ibid.). Some conceive of such organizations astextures of symbols or concepts (eg., Umpleby,1986). Furthermore, system theory and cyberneticshave brought to the fore theories in which communications are the constitutive elements of socialorganizations (mainly Luhmann, 1995). Broekstra(1998) has introduced the notion that ‘an organization is a conversation‘ based on which one canstate that social organizations are networks of conversations. Luhmann, who was profoundlyinspired by the ideas of Maturana and Varela, isthe main proponent of the new view of orgariizations, wbich centers on communication as the coreof social systems (Luhmann, 1995, 1997). For Luhmann, the operations of social systems are communications. The closure of the system is produced bycommunication in a circular manner: Communications trigger communications trigger communications and so forth (Lubmann, 1997).

The Operations of a System then are determined by a specific logic, which is embodied incodes that establish goals as orientators—orattractors—for the agents in the system. Forexample, in private firms, the goals are codified

Syst. Res. 29, 342—367 (2012)DOl: 10.1002/sres

344 Markus Schwaninger and Stefan N. Groesser


on a scale between profit and loss or, withina larger urne horizon, between viability anddecrepitude (Schwaninger, 2009). The respectivelogic of the system then materializes in operations aimed at attaining these goals. In otherwords, the emerging operations revolve aroundgoal attainment. In principle, the system is unableto change its orientation and has to function alongone and the same trajectory. In case it is irritatedby alternative orientators, it may vacillate, butthe system is still bound to relapse into followingthe given trajectory Transition to a different orientator occurs only if the perturbations are strongenough and enduring over a sufficient time.

A popular fallacy attributes the dynamics of asystem mainly to external forces (Richardson,2011; Sterman, 2000). Examples from the businesscontext: when sales are down, the weather isblamed for this situation. When an undesiredevent occurs, random forces are held responsible.When the emotional cimate in the organizationis unstable, it tends to be considered the management‘s fault. Systems science conveys a differentview: extensive studies in system dynamicsdemonstrate that the dynamics of systems aregenerated most often within the system (Sterman,2000; Richardson, 2011). When puzzlirig dynamicsor difficulties occur in a system, it is weil worthstudying the logic that generates the respectivebehaviour. The issue then is reflection.

Reflection is a deliberation at a higher logicallevel of an event or process that goes on at anobject level. In the context of operationallyclosed, autopoietic systems, a reflection is aninstance of self-reference, that is, it is about asystem poinfing to itseif. Luhmann (1995) distinguishes three levels of self-reference: first, band

self-reference, which is at the level of systemelements that are both cause and effect in a chainof events; second, reflexivity, which denotesthe reference of one comrnunication to anothercoinmunication; and third, reflection at the levelof the system, which is the system observing

what it does. In the following, we are going tolimit our discussion of self-reference to the thirdlevel—reflection—-which is the most powerfullever of self-reference regarding inducements forchange. Reflection is a mirror image if it consistsmerely in reflecting an object, but it can become

Copyright © 2012 John WUey & Sons, Ltd.

a major force to change the evolution of thesystem once the system thinks about itseif andits relationship with its environment. Reflectionhas the potential of leading a system onto anew orientator. Autocatalytic, seif-referential processes play a major role where perturbations leadto a new state of order (Jantsch, 1975; Prigogine,1976). In the next sections, we present a formalismfor the description of organizational processes interms of operational closure and self-referenceand then apply that formalism to a concrete caseof organizational change. From there, we constructa simulation study to gain further insights into theworkings of autopoietic systems.

FORMAL EXPRESSION

The basic diagram in Figure 1 depicts, in a classicalrepresentation mode, an operation closing in onitself, which constitutes the epitorne of operationalclosure.

An expansion of this scherne is provided by theinclusion of se]f-reference. The pictogram in Figure 2expresses the combination of organizational closure and self-reference in a parsimonious mariner.In the scheine, 0 stands for operation, 1? for reflec

tion. When addressing self-reference, as alreadymentioned, we focus our perspective on reflection.Arrows that transcend the bounds of the circlessymbolize transformative instances. On the onehand, reflection is apt to trigger a change in themodus operandi of the system, by expanding the

E Operation1

Syst. Res. 29, 342—367 (2012)DOl: 10.1002/sres

Figure 1 A symbol of operational closnre

Fignre 2 Pictogram für a seif-referential system (0 = operation, R = reflection)

Operational Closure and Seif-Reference 345


space of potential behaviours. On the other hand,the modus operandi can trigger changes in reflection, for example, by showing deficits in the adaptation of the operations to environmental needs. Inboth cases, a change of the System resuits. Onthe basis of a mono-causal view or a determmisticontology the implication would be that change iscaused. A multi-causal view or a non-determiriisticontology to which we adhere, suggests that changecan orily be influenced or triggered, not caused.

The process of change of the System i5 symbolized in Figure 3 with time on the horizontal axis.Here, S stands for the state of the System at different times t. lt is possible that qualitative changestransform a system significantly, eventually leading to a new system,D which is indicated by S, S‘,and 5“. R3 denotes reflection, which is the thirdlevel of seif-reference. The changes of System stateare brought about synergetically by both theendogenous dynamics of the system Operationsand the reflexive process. Both also influencethemselves, as the horizontal arrows in Figure 3show (see also the circular nat-ure of 0 and Rdepicted in Figure 2). The respective mode ofreflection leading to system change from 5 to 5‘(Figure 3) is introduced in the simulation studycarried out later.

The simulation model will demonstrate thatthe reflexive strand is often more influentialthan the internal dynamics of the operationsstrand. Seif-reference, including aspects suchas self-observation and self-description comingtogether in a process of reflection, are apt to trigger substantial change of the System and even tobring about a new system. We can now proceedto the case study, which forms the basis for therest of the paper.

APPLICATION TO PROCESSES OFORGANIZATIONAL CHANCE

The case study is described in the language wehave developed above. The case informs the

A new system could be, for example, a System dominated by a newparadigm. Parsdigm denotes a pattem of thoughts, mindset, practicesor convictions shared by a scientific community (after Kuhn 1996), aconcept which can be transferred to organizations in general.


conceptualizing of the ensuing computer simulation model and the pertinent analysis. The case isabout an organizational transformation accomplished in an irisurance company with which oneof the authors (M. S.) cooperated in bis functionas external fadiitator. At the time, the organization,which we call INCO, had about 4000 employees. ltwas part of a larger corporation but bad a highdegree of autonorny. We found that this autonomywas, to some extent, devolved ‘from above‘, but itcame to a large degree ‘from inside‘ as the consequence of a powerful identity that had stabiizedover the years as a product of operational closure.In the following, the organizational transformationwffl be described in five stages. Figures 4 and 5depict the process using the notation developedin the prior section. In Figure 4, iconic language isused; in Figure 5, the representation is a graph.Finally, the formulaic representation is applied tothe case.

Stage 1: Steady State

INCO ran its distinct operations and also badthe competence to define and implement itsstrategy, although strategy was not a topic ofrelevance to the managers. The cornpany washighly profitable and efficient, so much thatthere seemed no need for working on its strategies.The whole firm quasi-‘automatically‘ followed aset of proven rules, which governed recurrent,essentiafly ‘closed‘, operational processes followinga cogent logic. The imperatives were to increasesales, improve efficiency and achieve high profits,all in a setting of high-quality services, attractiveworkplaces and a well-motivated, cohesive workforce. Apparently, there was no need for changingthis well-established, operationally closed system.

Stage 2: Incipient Change

This placid situation was suddenly disturbedwhen the market, which had grown sturdily fordecades, stagnated and competition jumped up.This was first perceived by the marketing andsales people who were more aware of the immediate sales figures than about the fundamental

Syst. Res. 29, 342-367 (2012)DCI: 10.1002/sres



R3‘

/t5 t1 t2 t3

\/t4 f

“R÷ -‘0t QS S S 5‘ S‘ S‘tQ t1 t3 t4 t5 tß

Figure 3 A system changes as a product of operational dvnamics and reflection

SteadyState

• Efficient operationsover decadeswhole rmautomatically“ follows

a set of proven rules:• increase sales• improve efllciency

maximize profft

•Transformation ofthe system

•Implementing newstructureAdjustingmanagement systems

•Revising marketingapproach

• Empowerment ofpeople

p‘/t

\/t

—

°t 0 QSjg

s, s;

changes in the markets that began to show onthe horizon: A demand for customized solutions instead of merely standardized products,individualization, fragmentation, specializationand internationalization of the market, just toname a few. That on the market front was acrucial perturbation. lt was actually perceived bymany, but it took time until it triggered a reactionfrom the company, given significant perception


delays. The catalytic function, which induced aprocess of change rested with the chief executiveofficer (CEO) and his head of corporate development. These leading figures were aware of theemerging imbalance between the status quo andnecessary change. They monitored the signalshut were not very successful in transferring someof the new awareness to the high-level managers.There was too little channel capacity—that is,

Syst. Res. 29, 342—367 (2012)DOl: 10.1002/sres

1 ncipientChange

•lntroduction ofthe strategy teamas a °reflectivefunctionEstablishment ofadiscourse onstrategic andnormativemanagement

Decision toredefine rulesRedesign ofthecompany,especiaty strategyand structurePPan for change

1 1 11 1 1

Stage 1 to Stage 2: ti Stage 3 .. Stage..

Stage 5decades —1 year —1 year —6 months decades

Figure 4 The transformation process at INCO

St0

Figure 5 The transformation process at INCO represented as a graph. P stands for a perturbation or irritation

Operational Ciosure and Seif-Reference 347


the upper limit of the information that can betransmitted reliab ly through a communicationchannel (Shannon and Weavei 1949)—for raisingthe awareness of the need for change, and everyonewas too busy anyway to counter the orgarilzationalmertia. Meanwhile, the operational logic followedits path as ever. Over time, the need for a strategicapproach to conceptualize what occurred wasdiscussed occasionally and informally betweenthe head of corporate development and some ofthe managers. Then, the two catalysts, who wereperfectly aware of the need for change, pushed acorporate development project. Together with themanagement team, they embarked upon a strategic positioning and, if indicated, reorientation ofthe company. A project team of 15 top and highlevel managers was formed, and a small externalteam of consultants hired to support the project.The key facilitators in this venture were the internal head of the corporate development unit and,externally, one author (M. S.) as the project leaderon behalf of the consulting firm. This way, a discourse about strategy, its underlying principles,and values was brought to life. Reflections at thelevel of the organization as a whole becamepossible.

Stage 3: Analysis, Reframing and Design

The reflection process gained momentum fast.First, the concepts of strategy, which had beenlargely ignored before, were introduced to theproject group and assimilated by its memberseagerly. The discourse gained a new dimension:A new logic and a new language gained ground;long-term perspective, strategic positioning andviability of the firm were the new imperatives.That reframing led to a sequence of fluctuations,which ultimately entailed a new order (Prigogine,1976). To diagnose the strategic position, the project team carried out thorough analyses. Severalworkshops with the whole project team, includingthe external consultants were held, in whichresults were reviewed and the next steps defined.After a few months, it had become evident thatthe core competencies of the company lay in business transactions with corporate clients as well asin deaLing with complex insurance and risk


management issues. In addition, several important insights into different aspects of thebusiness—competitive posture, marketing andorganizational processes—had emerged. The project headed towards the design phase. Severalteams were formed to pursue key issues such ashuman resources, organizational re-design andthe configuration of distribution channels. Morepeople from these teams were mobiized for thesetasks. Also, team members started to diffuse intermediate results among their own staff, thus involving them in the knowledge-building anddecision-making process. The far-reaching decisions taken were as follows:

(1) to build the company around customer problems rather than products,

(2) to strengthen the business with corporateclients, and

(3) to expand the international business.

These decisions implied that a fundamentalorganizational transformation had to result. Thecompass pointed to a re-design of the organizationconceptually, based on the viable system model,which has been described elsewhere (Beer, 1979,1985; Schwaninger, 2009). The emphasis of theintervention was on the structuring of the basicunits and their management. The reorientationwas fundamental: it is no exaggeration to speakof a paradigm shift. The radical change to whichthe strategy team aspired, and which was eventually accomplished, is schematically visualizedinFigure6.

The traditional organizational structure wasaligned to functions. The main organizationaluriits, apart from staff units (i.e., human resources,finance, controlling, administration, corporatedevelopment), were four large departments: marketing, underwriting, claims and sales. The firstthree were centralized in the capital, the last hadabout 80 branches across the countrv, groupedregionally. The first three were sub-structuredaccording to product groups, of which, automotive insurance was the largest. The new structurewas to group the company activities around twobasic custorner problems, that is, the needs oftwo major customer groups, namely, individualand corporate clients. Before the decision torestructure was taken, its multifarious aspects

Syst. Res. 29, 342—367 (2012)DOl: 10.1002/sres



Traditional Structure

Sales

New Structure

Code:PG Product GroupAeg Region

and implications were thoroughly examinedfrom a variety of perspectives. The approachappeared to be robust in that the new plan wasboth desirable and feasible (Checkland, 1981).The structural change was at the core of the paradigm shift because it expressed a differentworldview and a new organizational culture;the company was heading at a fast pace towarda culture in which the customer was the mostimportant stakeholder, not the employees or theshareholders. The self-referential processes triggered by the catalysts of the change was the“engine“ of that development.

The delineation of the new borders of the basicunits was likely to be highly durable. The unitswere designed to be clearly identifiable businesses in their own right and viable organizationswithin the whole—relatively autonomous divisions equipped to maintain a separate existence(Beer, 1979, 1985). The redesign went beyond amere outline of a new strategy and organizationalstructure. First, it included a detailed plan for thetransition to the new state. Second, an intensive


communication process between the managersand the people in the organization provided thatnot only the implementation plans became highlyconcrete but also the people in the organizationwere ready to move. Indeed, culturally, it hadalready started to move (Schwaninger, 2006).The task ahead was also to move the organization‘s structure.

Stage 4: Transition

The cultural transformation was already in full advancement. After the conclusion of the consultingmandate, INCO executed the new plan. Almostevery employee in the company was affected,most people to a large extent. The speed of thetransformation was astonishing. The structuraltransition of the organization was accomplishedwithin six months. People were transferred, locations were transmuted, equipment bad to bemoved and 300 computer applications werecompletely changed or overhauled. After these six

Syst. Res. 29, 342—367 (2012)DCI: 10.1002/sres

Marketing

Figure 6 Structuring of basic units



months, about 85 per cent of the staff had new

superiors, and most employees had to think along

different lines.At first, the transition did not comprehend all

the changes as mapped out. In the first phase,the subunits in the new divisions were structured

along traditional product lines. Later on, a group

ing into business units according to more specific

customer problems or client groups would be

relatively easy. There were some questions of

demarcation, although of secondary importance:

‘Should small business be part of the first or of

the second division?‘, ‘Should farmers be attended

to by a separate business unit, and where should

this be located?‘ and ‘15 a new division that

attends large multinationals necessary?‘As far as the sales organization was concemed,

it maintained its regional structure. However, in

all regions, a specialization between individual

and corporate clients was pursued. The claimsdepartment was re-organized in the first phase

by means of an internal differentiation between

individual and corporate business.lt was surprising how fluent the organization

had become in taking on the new rules andlanguage. Certainly, the facilitators had contribu

ted greatly—less through direct intervention than

through the design of communication and diffu

sion processes, which catalysed reflexive processes

into the subunits. After all, that was their function

as the epitome of the corporate refiection function.

By the end of the fourth stage, the operations

within the new structure were already on the

verge of perpetuating the new logic. A new para

digm, that is, collective mindset, and a new modusoperandi had taken effect.

Stage 5: Further Evolution

After the change project, the new logic consoli

dated and eventually dominated the organization.

Over the following years, INCO evolved unceas

ingly without any great transition. Some of the

changes initiated in the transition phase werecontinued. To take two examples, first, the inter

national business was developed into a separate,autonomous division. This step was taken within

about two years after the project. Furthermore,


the component subsystems of the sales organiza

tions were integrated into the individual and

corporate divisions, respectively. In the followingtwo decades, INCO went through three major

reorganizations, one every seven or eightyears.

These all were cases in which path-breaking selfreference had led to a new paradigm. The com

pany has not changed its basic strategy, that is,being an overall insurer with a leading position

in the corporate insurance market and interna

tional business. As a whole, it has shown a great

deal of adaptiveness, being grounded in selfreferential processes. In the phases between the

reorganizations, the new structures were stabi

lized by efficient processes of organizational

closure.Follow-up interviews conducted after a reason

able five-year interlude following our project

showed surprising results. The whole transforrna

tion had been realized smoothly and without

noteworthy resistance. Practically, all members of

the company had embraced the new orientation

and adapted to it quite easily. In terrns of strategy,

the intended strengthening of the positions inthe corporate and international domains was acomplete success. This had led the top manage

ment at the group level to adopt a similar organizational model. A reorganization of the

corporation had taken place at two levels of recursion, company and group.

Early on in the new milennium, 20 years afterthe project, one of the authors (M. S.) approached

the CEO of the group for a second follow-up. Theinterviewee commented that the original project

had been the bedrock upon which the foundationsfor a new orientation had been laid. The companyand its management had leamed a new approach

to strategy and organization, which was the keyfactor in the rise of the group and its international

projection as a financial service organization. Selfreference was the key to evolution, operational clo

sure the mode of implementation. Viabiity andprosperity have been the consequence.

To surnmarize, the transformation process

observed in this case comes dose to the ideal typeof a ‘teleological‘ change process—a process inwhich a problem or opportunity is perceived and

acted upon purposefully (Poole et al., 2004), withthe special feature of a participative, cooperative

Syst. Res. 29, 342—367 (2012)DOl: 10.1002/sres



mode developing the unifying goals and strategies.However, it also carries characteristics of the ‘evolutionary‘ process type, with variation, selection andretention as the drivers of change (ibid.). This latteraspect has not been arialysed here in great detail,but it consistently underlay the pattem of charigefrom an extant to a new paradigm.

SIMULATION MODEL OFORGANIZATIONAL CHANGE VIA SELFREFERENCE

In the following, we develop a simulation modelthat operationalizes the logic of a seif-referentialsystem. For this, we use a higher-ordei differential equation model, which we simulate to obtaininsights about the basic properties of operationalciosure and its interplay with self-reference. Themodel will function as an insightful descriptorof organizational change processes. lt has beendeveloped to demonstrate under what conditionsan established paradigm can be displaced byan entrant paradigm. The simulation model is acausal process theory about paradigm changebased on self-reference as laid out in the first partof the paper and the subsequent case study. Weuse system structure diagrams to detail the partsof an organization that generate operationalclosure, paradigm evolution and paradigm consolidation as weil as to estimate the impact thatself-reference can have on paradigm transition.Thereafter, we simulate the system model andanalyse its behaviour. Finally, we derive insightsbased on experimentation using the simulation.We develop the structure of the System model infour parts by unfolding the main dynamic thatexists with relation to our operational closure andseif-reference paradigm in the light of evolutionand paradigm transition. The simulation methodologv used is system dynamics.6 The followinggraphs show ‘System sfructure diagrams‘ or ‘hybrid

6 System dynamics (SO) is a methodologv for the modeling and simulation of complex systems, developed by Prof. Jay Forrester at MIT,and grounded in Control Theory as weil es in the modern Theory ofNonlinear Dvnamics (see: Forrester 1961; Sterman 2000). The focusof SD is on issues, which are modeied 55 Systems made up essentiallyof stock and flow variables forming c]osed feedback Ioops and simuIated as continuous processes. The mathematics of the models is basedon differential equations.


diagrams‘ (Groesser & Schaffernicht, 2012; Sterman,2000), that is, slightly simplified stock-and-flowdiagrams, where rectangles denote stocks (also:‘levels‘) and valves denote rates (also: ‘flows‘).Parameters are written out in capitals, auxiliaryvariables with small initial letters.

Structure Part 1: Basic Operations in theExisting Paradigm (Figure 7)

The day-to-day activities of an organizationcan be represented by tasks. Tasks required is astock variable, that is, an accumulation or buffer of activities, which have to be fulfilled toachieve the purpose of the organization. Thesetasks are, for instance, development of new products, formation of new affiiates, or hiring andtraining of employees. The stock is changedby its rate variables. The one that adds to Taskrequired is the rate nezv tasks. This demonstratesthat new activities are required every period tosustain the current level of the organization.The level of Tasks required is reduced by taskexecution. In case the tasks are executed successfully, that is, to a satisfying degree relative to therequirements of the environment, they movefrom Tasks required to the level Tasks snccessfiulyJlilfihled. This is the normal process ongoingevery day in organizations. The stock Tasks successfiuly fiulfilled is depleted by discarding tasks,for example, customers who discontinue therelation with the organization or researchefforts about mature technology, which becomeobsolete. To sustain the self-production of theorganization, these tasks have to be renewed,for example, new products have to be designed,customers acquired, and employees hired. Thisprocess operationalizes the concept of operationalclosure as defined in the first section of thispaper; tiere, we capture it in the ioop OperationalClosure (R).

The successful execution of tasks depends onthe available competencies of the organization.The higher the level of Coinpetency in the established paradigin (EsP), the more efficient is theexecution of the tasks that are completed successfully. In addition, the more tasks are successfullyexecuted, the more proficient the organization

Syst. Res. 29, 342—367 (2012)DOl: 10.1002/sres

Operational Closure and SeIf-Reference 351


becomes regarding this competency base in the

established paradigm. This execution and leam

ing process forms a virtuous circle of success

(R1). To complete the picture, the competencies

are also lost over time by organizational forget

ting—represented by the rate forgetting. Besides

completing the tasks successfull) they can also

be completed unsuccessfully. These tasks then

accumulate in the stock Tasks not fulfilled and

latent. They are latent and hence not known to

the orgariization. With significant time delays, it

is likely that these unsuccessfully executed tasks

are discovered and are then Tasks notfufihled and

known. This difference between the statuses of

unfulfilled tasks—latent and known—is of crucial

relevance for understanding the counterproduc

tive dynamics that unfold in an operationally

closed system. The degree to which Operations

are executed successfully in the first place is lar

gely determined by the requirements of the

environment with regard to the established

paradigm. If there is a strong correspondence of

the established paradigm to the external require

ments, the adequacy is high and leads to a

successful completion of the tasks, leaving only

a few of them as completed unsuccessfully. How

ever, as the environment evolves over time, the

requirements on the operational level change,

for example, the requirements change from

product innovations to process innovations to

service innovations (Utterback, 1994). The case

study in the previous section has described an


exemplar of how an existing organizational para

digm can become obsolete. The more inadequate

the existing paradigm becomes for executing the

tasks required, the lower is the share of the

successfully completed ones and the higher is

the share of unsuccessfully executed tasks, lead

ing to unfulfilled tasks—both latent and known

(Figure 7).The principal ioop Operational Closure (R) will

be crucial throughout our following discussion;

without it, the organization would cease to exist.

Because the purpose of our elaboration is to

detail the dynamics of paradigm evolution, para

digm transition, and the effects of self-reference,

we can safely exclude the flows neu; tasks anddiscarding tasks in the following Figures 8—10

without losing generality.

Structure Part 2: Evolution of an Entrant

Paradigm (Figure 8)

Besides the established paradigm, entrant para

digms (EnP) evolve. Here, we consider only one

of them, which is capable of addressing the whole

range of requirements of the environment. Hence,

this entrant paradigm is more powerful than the

established one. lt fulfills the tasks required and

can, in addition, solve the remaining unftilfilled

tasks. In principle, the entrant paradigm evolves

by the same seif-reinforcing learning mechanism

(R2) as described before (R1). However, at the

Syst. Res. 29, 342—367 (2012)DCI: 10.1002/sres

Figure 7 Operational closure (R) ensures the self-production of the organization. This is operationalized by a simple task

co;npletion cham with successfu ly and unsuccessfully executed tasks zuithin an established paradigm


Syst. Res. RESEARCH RARER

Competencies

_________

I‘- in establishedlearning EsP paradigm (EsP) forgetting

__

Lng____

ACTUAL ADEQUACY OF successfullyESTABLISHED PARADIGM + executed tasks EsP

Tasks not Tasks not TasksTasks required fulfilled & —l fulfilled & siicceSSfUlIy

unsuccessfully 1 latent discover known si,e fulfilledexecuted tasks EsP „z_

successfullyexecuted tasks EnP

++.P Learnin)

learning EnP 1 CompetenciesV ..( in entrant

paradigm (EnP)

Figure 8 Tasks not Jlilfilled are a result of inadequate task execution within the established paradigm. These tasksprovide the ground for a powerful entrant paradigm to develop

beginning of the developrnent, the learningcycle R2 is weak compared with R1 of the established paradigm because the entrant paradigm


is new and immature. However, once the entrantparadigm would gain experience and becomepowerful, it would substitute for the established

Syst. Res. 29, 342—367 (2012)DOl: 10.1002/sres

Figure 9 The System‘s lock-in structure. The experience in the existing paradigm resuts in an organizational lock—in andblindfolds the organ ization, preventing an adequate aligmnen t with its enviromnen



paradigm. Then, the flow successfully executedtasks EsP would disappear, and the successfullyexecuted tasks EnP would complete the taskswithout a significant number of failures. However, as we have pointed out in the first part of

the paper, the transition of an organization‘sparadigm is an undertaking that causes frictionand resistance. An organization‘s core competencies7 are the basis for its adaptiveness, andthey must be developed over time (Utterback,1994). Hence, we could not explain the transition of paradigms if we were unable to accountfor the resistance dynamics of the establishedparadigm, which perseveres to prevent itsdispiacement by the entrant paradigm. In thefollowing, we detail those behavioural aspectsthat result in policy resistance and therebyanswer the question: Why is the new paradigmnot embraced, although it is more capable ofcoping with the requirements of the changing

environment?

Core competencies are those factors, which enable art organization tocreate ‘alue for custorners and achieve sustained competitive (and collaborative) strength or advantage (See also: Prahalad ei al., 1990).


Structure Part 3: Resistance Dynamics of theEstablished Paradigm (Figure 9)

The resistance to change of the established paradigm can be explained by a multi-loop feedbacksystem. An increasing base of competencies inthe established paradigm, coupled with an increase in the number of successfully fulfilled tasks,leads to the perception that the paradigm isadequate to the environment‘s requirement. Only

a significant number of unfulfiled and knowntasks could invert this perception. Initially, however, the related stock Tasks notfufilled arid knozvn

is virtually zero. Consequently, the task-executingorganization learns and develops competencies

(REl) and, because of the absence of any otherindications, also retains confidence in its established paradigm. The evolution of confidencecould be influenced by a powerful entrant paradigm, which, in the beginning, does not exist.Hence, increasing levels of confidence limit theorganizational possibilities to perceive the truebenefits of other paradigms; the dominant modeis one of organizational (self)-confirmation andnot one of experimental reinvention (Nelson &

Syst. Res. 29, 342—367 (2012)DCI: 10.1002/sres

Figure 10 Seif-reference as a catalyst of change and balance in an organization. Thefeedback rnechanism R7 and B1 can heipto overcome Organizational lock-in (R3) and Blindfolding (R4)



Winter, 1982; Sastry, 1997). This perception biasfuels two powerful mechanisms: OrganizationalLock-in (R3) and Blindfolding (R4).

Because the perception bias devalues the trueeconomic and social benefits of the entrant paradigrn, the organizational members are discouragedfrom leaming about this paradigm hindering thecreation of competencies. As a result, the entrantparadigm cannot build up strength and cannot beapplied to solve tasks. Consequently, the onlyway to fulfill the required tasks is by means ofthe established paradigm. This feedback mechanism is active from the beginning of the development and cements the status quo, with the sideeffect of preventing competing paradigms fromarising (R3). When only the established paradigmis utilized, the continuous development of itscompetency base (R1) leads to the effect of organizational lock-in, that is, ‘allocations gradually rigidify‘ (Arthur, 2000: 28). Put differently, the hurdiesfor an entrant paradigm to enter the organizationincrease exponentially (R3). Let us flOW assumethat the adequacy of the established paradigmbecomes smaller as time progresses.8 The efficiency with which it fulfills the tasks is thenreduced; it still resuits in successfully executedtasks but, at the same time, also in a growing nurnber of unsuccessfully executed tasks, which arelatent at first.

The second powerful impact of the perceptionbias is that it reduces the organizational capabilities for detecting latent unfulfilled tasks (R4), bydiminishing the rate at which they are discovered.Consequently, R4 renders ineffective the onlystructural measure, which the organization hasfor countering an inadequate development of itsparadigmatic direction, resulting in higher confidence in the established paradigm and even stronger miSperceptions of others.9 Both reinforcingcycies decouple the organizational perceptionfrom reality, predetermining a strong and severedrawback if this aberration is not corrected.Given the described evolution, no countervailing

This is implemented by a gradient over time, in the values of ActualAdequactj of Established Paradigni.

See the following causal loop: perception biss—. (—) discover— (+) Tasksnotftilfihlcd and known—‘ (—) Perceived adeqirncy to environn,ent— (+) con—

fidence in esfablished paradigni—. (+) perception biss. The product of allpolarities is (+).


paradigm can gain enough strength to balancethe over-confidence in the established paradigm.Moreover, the evaluation of a new paradigm‘sadequacy is performed within the perspectiveof the established paradigm. This flaw results ina rigid organizational outlook, which is unable tonavigate into beneficial futures. The Blindfoldingloop (R4) is especially powerful because it fosters a situation in which organizational members do not know that they do not know(‘double-blindness‘). The feedback loop R5 actsas an additional virtuous cycle, which boostsconfidence in the established paradigms exponentially to overly high levels; it reinforcesthe already ongoing development.

Let us assume that the environment has changed slowly but steadily within a significant timehorizon. At such a point in the organization‘sfuture, the established paradigm is not adequateanymore. Given steady behaviour by the environment, even the obvious inadequacy of theparadigm does not lead to a paradigm changebecause, first, no alternative paradigm has survived and had enough strength to substitute forthe established one. Second, the inefficiency ofthe established paradigrn is not perceived bythe organization itseif because the stock of tasksuizfiifilled and latent, although large, goes undiscovered. In such cases, incremental changes inwhat the environment requires leave the adequacvof the paradigin unchallenged.

However, if change in the environment is radical and comes relatively early in the developmentof the organization‘s life, then a disruptive burstdestabilizes the organization‘s fitness landscapesignificantly. The established paradigm becomessuddenly inadequate; a large number of taskscannot be fulfilled satisfactorily anymore. Becausethe competencies in the established paradigm andthe tasks successfully ftilfilled have lower levels,confidence in the current paradigm goes down,with lower perception biases. In such a setting,the mechanism.s R3, R4 and R5 would be ratherweak. Hence, tasks which are not fulfilled wouldbe discovered much faster. Then, it would becomeobvious that the adequacy of the established paradigm is questionable. In this case, leaming with anew paradigm would be possible and wouldresult in successful task execution and problem

Syst. Res. 29, 342—367 (2012)DOl: 10.1002/sres



solving. The learning process (R2) would fuel thecompetencies in the entrant paradigm, leadingto a successful dispiacement of the establishedparadigm.

Both of these developments can be summarizedas the boiling-frog syndrome—the organization willremain in a paradigmatic steady state when theenvironment‘s rate of change is below a certainthreshold; beyond the threshold, the organizationwill adapt its paradigm to the environment‘srequirements. Here is where the concept ofself-reference provides an important lever. Seifreference is an organization‘s second receptor forthe current state of the system. lt should enablethe organization to overcome the organizationallock-in dynamics as described before. The nextsection will detail the respective mechanisms bywhich this can happen.

Structure Part 4: Enabling the OrganizationalParadigm Transition (Figure 10)

Seif-reference is, as has been detailed in thispaper, a competency in deciphering, criticizingand changing the rules that influence the behaviour of the system. In Figure 10, self-referenceis a meta-level measure, a meta-competence, forcontrolling the organizational reality. The levelof seif-reference of an organization is improvedby external perturbations, internal perceptions,or a reflection process (R6). lt is stimulated whenthe organization realizes that tasks are notfulfilled adequately. Self-reference is learned,which then results in improvements in the rate atwhich unsuccessftil tasks are discovered (R7). Inaddition, increments in the level of self-referencealso stimulate leaming effects in the competenciesof an entrant paradigm and increase the rate ofsuccessful task solving. To summarize, theconcept of seif-reference acts as a meta-levelcontrol loop (BEI) to align the organization withits environment—with the side effect of developing competency in the entrant paradigm (R2).

Now that we have detailed the system structure, we also want to point to some of its limitations. We have concentrated solely on competingparadigms (Senge, 1990; Sterman & Wittenberg,1999). In reality, there are also paradigms, which


coexist in symmetrical-symbiotic or unsymmetrical predator—prey relationships (Pistorius & Utterback, 1997). These forms of interaction would bestbe discussed in future research. In addition, wedetail in this model the transition between twoparadigms; future research might generalize it ton-interacting paradigms, which is assumed to bea demanding task (also Sterman and Wittenberg(1999) use only a limited nurnber of paradigmsfor explicatory purposes).

Sirnulating the ModelHaving detailed the structure of the systemunder study, we are now going to simulate it inthe following. First, we show the case of an organization, which is locked in the established paradigm, and demonstrate that a short-term externalperturbation is not sufficient to break the existingparadigm. The second case demonstrates a successful displacement of the established paradigmby means of a sufficient perturbation. Based onthese first two cases, we are motivated toexperiment with the mathematical model tounderstand its tipping point dynamics and thesensitivity of the tipping point. The model is simulated over two years (720 days).

Case 1: Dominance of the EstablishedParadigm—Entrant Paradigm Fails

In this case, the organization has a bw level ofself-reference (R6, R7 and BEI are not significant).Given this situation and based on the establishedparadigm, tasks are executed successfully, competencies are accumubated (REI), and confidencein the established paradigm arises, beading tostrong perception biases, which confirm theestablished paradigm (R3, R4, R5) and thwartevidence of mismatches from becoming obvious.An entrant paradigm cannot gain strength byitself—R2 is not active (Figure 11). The evolutionof the state of the system is smooth and continuous. As indicated in Figure 11 (right hand side),the organization is locked-in; hence, the systemchanges only within the same paradigm 5‘.

lntentions to change die established paradigm insuch a situation require an extemal perturbation.

Syst. Res. 29, 342—367 (2012)DCI: 1Q.1002/sres



E100fEstablished Paradigm

tJ,

0

Entrant Paradigm

stn,

0 80 160 240 320 400 480 560 640 720 0 80 160 240 320 400 480 560 640 720

Day Day

Figure 11 The established paradigm dominates the System; OH entrant paradigin cannot gain strength. The state of the systenlevolves incrementally towards equilibriuni, which indicates a complete organi:ational lack-in

This might be achieved by the application ofexternal seif-reference capabilities. The intensiveperturbation begins at t = 150 [days] with a duration of 20 days. Thereupon, the competencies inthe entrant paradigm can gain strength (Figure 12).When the perturbation ceases, the paradigm has toprosper based on its own momentum (R2). However, this momentum is not strong in relation tothe forces suppressing it (R3, R4, R5). Consequently, the competencies that have been built updissolve over time—the organizational lock-in ofthe established paradigm could not be overcome;the state of the System (Figure 12) follows the sametrajectory as in Figure 11.

Case 2: Displacement of the EstablishedParadigm—the Entrant Dominates

Given enough resources to sustain an externalperturbation for a longer period, what might be

the result on the changes in paradigms? Toanswer this question, we simulate an externalperturbation with duration of 60 days, threetimes as long as the perturbation in the first case.

The perturbation (60 days, Figure 13) starts att = 150 here as weil. Figure 13 shows that untilt = 210, the competency level of the entrant paradigrn is pressed to a level of nearly 50. Then theperturbation ievels off. However, this externalsupport has been sufficient to create a momentumin the organization that can now be self-sustained.R2 continues to improve the competencies in theentrant paradigm; higher levels of seif-referencelead to a discoverv of more unfulfilled tasks,which are subsequently completed in view of theentrant paradigm. In addition, R6 and R7 areactive in improving the level of seif-reference,transforming the organization into a highly seifreferential System. After t = 230, the establishedparadigm is displaced by the entrant paradigm,

0 80 160 240 320 400 480 560 640 720 0 80 160 240 320 400 480 560 640 720

Day Day

Figure 12 The external perturbation resuits in a short—term improvenlent ofthe competenciesfor the entrant paradigm. Thisintervention, howevei cannot gain enough strengtit internally to challenge 11w establislzed paradigm. The system reninins an

11w same trajectort/

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. 29, 342—367 (2012)DOl: 10.1002/sres

E 100

ca

75

0

w>ca-Jca0c

25

0.E0() 0

50

Established Paradiqm

External Perturbation

ca

cnca

0caca0

s,n,

EntrantParadigm -



E 1000)

75,

0

w50

-J

o25

cl,0.

0o 00

Figitre 13 A perturbation of 6Odays is szfflcient to break the organizational lock-in and change the trajectory of the organization front S‘ to S“. The established paradigm loses its superior position and fades in the long-term

at first gradually, later abruptly. This is alsoindicated by the transition of the System statefrom S‘ to S“ (Figure 13). The external perturbationhas successfully enlivened the seif-referential process of the system with a subsequent paradigmchange. The System has become a different one.

ExperimentationThe previous cases indicate that the system hasemergent bifurcation properties. We analyse thesimulation model using a univariate sensitivityanalysis (n = 100,000 simulations, uniform distribution, with durations D[0; 720]{days)). Figure 14shows an insightful subsample of this analysis.The bifurcation threshold is approximately atD = 22.8 days after the beginning of the perturbation. Perturbations with durations shorter than

this threshold cannot build enough strength ofthe entrant paradigm to seif-sustain it internallyin the organization.

For the sensitivity analysis in Figure 14, wehave started the perturhation (or intervention) att = 150 for all cases. A further interesting questionare as follows: how the duration, D, of the perturbation is related to the perturbation‘s startingpoint, t1, and how both hifluence the bifurcationthreshold? This is what we analyse next by anadditional extensive Monte Carlo simulation withthe following setup: n = 150 000 simulatioris, DE[0; 720], t [0; 400], final time of the simulation,T= 720; t Ø[400; 720] especially because fort,> 400, the development of the eritrant paradigmis not completed by the end of the simulation.From the analysis, we obtain a positive, continuous and curvy relation between the start time ofthe perturbation, t, and the required duration ofthe perturbation, D, required for dispiacing theestablished paradigm. The curve represents thetipping points between the areas of ‘entrantparadigm dominates‘ and ‘established paradigmdominants‘ contingent on Start time and durationof the perturbation. From Figure 15, it becomesobvious that the earlier the perturbatiori occurs,the less its duration has to be for the establishedparadigm to be overcome. This is comprehensible,given the feedback mechanisms described previously. We can also see that the relationship is highiynonlinear. This is because of the complex interactions of accumulations, duration of perturbation,learning dynamics, and timing of perturbation asweil as the adequacy of the established paradigm. Two implications can be derived. First,

Syst. Res. 29, 342—367 (2012)DOl: 10.1002/sres

80 160 240 320 400 480 560 640 720 0 80 160 240 320 400 480 560 640 720Day Day

100

75fcl)

‚-0)

50

25-

Eo0

ol0 80 160 240 320 400 480 560 640 720

Day

Figure 14 A sensitivity analysis uncovers a bftircationdynanuc. In the specification usedfor this paper, the tippingthreshold is approxiniately at 22.8 days after the beginningof the perturbation or intervention, which occurs at t = 150




40

35 Entrant paradigm dominates2.c3O:.2 •

25

5t20

15 Eatablished paradigm dominateso 10

.5 5 .o

00 50 100 150 200 250 300

Start Time of Perturbation [Oay]

Figure 15 An extensive Monte Corlo sinnilotion exlnbits thot the tipping point for parodignz disploceinent depends signzficontly on the duration ond Ute start tinte ofthe perturbotion. The eorlier the intervention, the niore efficient it will be. A lote

intervention is most fficient ott = 165

overcoming established paradigms becomes moreexpensive the longer the established paradigm isreinforced, up to the point where a change inparadigm becomes virtually infeasible (t > 300).Second, it is beneficial from an efficiency view topay attention to the dispiacement threshold. Forexample, from 150 < t < 180, the effort of theintervention required to initiate a paradigm displacement remains approximately constant; hence,in this neighborhood, waiting with interventionswill be beneficial. The reason is that adequacy ofthe existing paradigm decreases during this period, thus siowing the intensification in thetipping threshold, that is, the time required toovercome the estabhshed paradigm. During theperiod from 90 to 150, the effort to dispiace theestablished paradigm, although relatively high,even diminishes. This is because the learning thattakes place during this period is fastei as asignificant body of unfulfilled tasks has alreadyaccumulated, which is then reduced quickly,leading to a steep increase in the competencies inthe entrant paradigm. The ideal point in time fora latest but by then most efficient interventionbecause of these dynamics would be at t = 165.

We notice that we have always assumed idealperturbations, that is, perturbations of maximalstrength from the start of the perturbation (astepwise increase of 100 is introduced withoutsignificant delays, see Figures 12 and 13). Hence,with our assumptions, the effects of external perturbations on self-reference and the organizationaldynamics are overestimated. To compare perturbations with more realistic assumptions regarding


delays and strengths, it is necessary to caiculate theeffective force of the perturbation. Expressedmathematically, it is the integral of the perturbation from t to ti+D, with D as the duration of theperturbation. For example, an increase of D from20 to 60 results in a threefold effective force of theperturbation or intervention. 0

To summarize, it is most likely that thechanges of established, locked-in paradigmsare triggered by external events, for example,disruptive changes of the environment, or byintenrentions, which increase the level of selfreference and hence kick off paradigm-transitiondynamics.

DISCUSSION AND CONCLUSIONS

We have found that the concepts of operationalciosure and self-reference are indeed relevantfor the inquiry into organizations. Not surprisingly, our attempt to make these highly abstractconcepts palpable has borne the fruit of higherconceptual clarity more at the end of ourarticle than at its beginning. We have definedoperational closnre as fundamental property ofan organization, which produces and sustainsitseif on the basis of its elementary operations.The concept of setf-refere;tce has been considered,

10 The first case: 0 = 20 [daysl with 100 compelence units each day,resulting in an effective Farce of Hie perturbation = 2000 competencyunita. The second case: 0 = 60 tdays] with 100 competency units eachday, resulting in an effective farce of the perturbation = 6000 competency units.

Syst. Res. 29, 342—367 (2012)

DOl: 10.1002/sres

Operational Ciosure and SeIf-Reference 359


iii regard to the organizational context, in the senseof reflexive activities or roles, which deliberate onprocesses at an object level frorn a higher-levellogical stance. We have proposed a formal conceptual framework for a parsimonious expression ofthese concepts and applied it to both a qualitativecase study and a simulation model to captureessential properties of organizational change.Based on the case study and the simulation, wecan now draw conclusions for organizational practice. These conclusions are not the product of a‘forceful syllogism‘ (as Aristotle would call it) hutinsights, which have emerged during the processof our inquiry:

The Coupled Roles of Mindset and Autonomy

Operational ciosure is a generative rnechanismthat can produce organizational autonomy. Fromthe Greek roots autos (seif) and nomos (law), wecan infer that an autonomous system is a lawunto itself. lt determines its own rules of operation and governance. One strength of operationalclosure is in the adherence to established values,procedures and interpretations, in short, a paradigm, which reinforces and consolidates identity.In addition, it is precisely this identity, whichconstitutes the ultimate ernbodiment of a system‘s autonomy. The ultimate strength of anorganization‘s autonomy, then, is in leveragingthe meaning jointly defined and given to thesystem by its members. Addressing the questionof meaning in the organization is more importantthan most of the other tasks of management. Inother words, it is the shared mindset that governsthe fate of an organization.

A Different Light on OrganizationalTransformation

In principle, joint mindsets tend to be stable. Theycan be a formidable strength in shaping thebehaviour of a social system in the self-activating,recursive, seif-stabilizing process of paradigm

change. However, they are also a main factor of

organizational inertia and resistance to change.

The power of an operationally closed System can


become a weakness when a new situation calls foradaptation. Under such circumstances, autocatalytic forces are needed that trigger change. The sourceof such forces lies iii the domain of neither matternor energy but in the domain of information, communication, knowledge, understanding and wisdom; the key to transformation is seif-reference.lt is the main force that can change the endogenousdynamics of an organization and lead to paradigmtransition.

A Complexity View on the Dynamics of Change

Organizational change is often designated as acomplex process. We have studied a concrete organizational transformation, capturing its complexity by concentrating on two distinct butcomplementary angles: operational closure andseif-reference. Beyond that, we have fleshed outthe transformation phenomenon in a simulationmodel, which builds on the case study, but can beconsidered rather general and reaching beyondour specific case study. The resuits of our experiments with the model have, in particu1ai highlighted that the pattem of paradigm change canbe anticipated. We have also shown that paradigmchanges are not only triggered by disruptions inthe environment, hut can also, and at least asmuch, be facilitated by interventions that enforceself-reference. The ideal timing—operationalizedby starting point and duration of the perturbation—of such interventions can be estimated as afunction of the dynamics of the system understudy. Also, the intensity of interventions can beascertained. The evolution of a new paradigmdoes not necessarily lead to its domination. Theprocess is highly non-linear. Bifurcations can arisealong the way, and are likely, if the interventionsare not properly ‘dosed‘ in terms of timing andintensity. Beware, however, because the thresholdto transition is a tipping point, and paradigmchange can also go ‘the wrong way‘, that is, contrary to expectations.

In addition to the analysis given here, ourresuits could also be discussed in terms of a number of theoretical concepts, for example, resistanceto change, punctuated equilibrium, breakdown,knowledge assimilation and strategic leadership,

Syst. Res. 29, 342—367 (2012)DOl: 10.1002/sres


1


but that is not possible because of limited space.Our initial question was if operational closttreand seif-reference are insightful descriptors of processes of organizational change. We carinot claimthat the analysis based on these concepts leads toentirely different conclusions than studies basedon other frameworks, as they can also be foundin qualitative research (e.g., Pettigrew andWhipp, 1991, Floyd and Woolridge, 2000, Gioiaet al., 2010).

In any case, we can claim that our study isdifferent from ‘the easy research that relies onsurveys and public databases [whichj is verylikely to discover empty c1ichs and superficialrationalizations‘ (Starbuck, 2010: 1398) and is paramount in mainstream research (Parnas, 2007).‘Researchers can learn things that are more realistic by using methods that penetrate faades‘(Starbuck 2010: 1398). Our contribution is specialin its systemic-cybernetic approach and therefore offers, in our view, a valuable complementto the mainstream works.

The findings in this article justify the claim thatthe descriptions based on the systemic conceptspresented here have ‘penetrated faades‘ in thatthey provide a broad, holistic perspective oncornplex processes: We observe an organizationalprocess as a whole, with the analysis hinging ontwo lead concepts only, and do not delve intoadditional analytical details, such as the analysisof self-referential sub-processes or the descriptionof decisions or structural changes in differentareas of an organization. In this way, severalnew insights have been gained, namely, by leveraging the complementarity of qualitative andquantitative analyses as synthesized in the paper.The core concepts of our study, operational closure and seif-reference, have lent themselves toan operationalization, therewith tightly couplingthe case study and the simulation model. Theseconcepts facilitate parsimonious formulations,and that might explain their power for analyzingcomplex Systems on both the qualitative and thequantitative tracks.

We trust that the evidence from our analysis leadsto a better understanding of the structures underlying the diange within organizations with the heipof the systeniic concepts organizational ciosure andself-reference. We must preclude a fragmented


picture that would focus on partial aspects orily.By adopting a holistic stance, we try to capturethe paradigm-transition process as an encompassing pattem of change pervading the whole organization. The systemic concepts applied here areparticularly appropriate for studying organizations as wholes.

REFERENCES

Ackoff RL. 1981. Creating the Corporate Future: Plan ofBe Planned for. Wiley: New York.

Arthur WB. 2000. Increasing Returns and Path Dependencein the Econoniy. The University of Michigan Press: AnnArbor.

Bailey KD. 1997. The autopoiesis of social Systems:Assessing Luhmann‘s theory of seif-reference.Systems Research and Belrnvioral Science 14(2): 83—100.

Beer 5. 1979. The Heart of Enterprise. Wiley: Chichester.Beer S. 1985. Diagnosing the System for Organizations.

Wiley: Chichester.Bolander T. 2009. Seif-Reference. In: Zalta E (Ed.)

Stanford Encyclopedia of Philosoplni. Stanford University: Stanford, CA. http: / /plato.stanford.edu/entries / seif-reference, retrieved Feb. 16, 2011.

Broekstra G. 1998. An Organization Is a Conversation.In: Grant D, Keenoy T, Swick C (Eds.), Discourse andOrgan ization. Sage Publications: London.

Bullinger HJ, Spath D, Warnecke HJ, Westkämper E(Eds.) 2009. Handbuch Unternehmensorganisation:Strategien, Planung, Umsetzung. Springer: Berlin.

Checkland PB. 1981. Systems Thinking, Systems Practice.Wiley: Chichester.

Floyd SW, Woolridge B. 2000. Building Strategy froin theMiddle. Reconceptualizing Strategy Process. Sage Publications: Thousand Oaks.

Forrester JW. 1961. Industrial Dynanucs. ProductivityPress: Cambridge MA.

Gioia DA, Price KN, Hamilton AL, Thomas JB. 2010.Forging an Identity: An Insider- Outsider Study ofProcesses Involved in the Formation of OrganizationalIdentity. Administrative Science Quarterly 55(1): 1—46.

Groesser SN, Schaffemicht M. 2012. Mental Models ofDynamic Systems: Taking Stock and LookingAhead. System Dynamics Revieu‘. DOI:10.1002/sdr.476

Jantsch E. 1975. Design for Evolution: Seif-Organizationand Planni;zg in the Lfe of Human Systems. Braziller:New York, NY.

Jantsch E. 1980. The SeIf-Organizing Llniverse: Scientficand Human Implications of the Emerging Paradigin ofEvolution. Pergamon Press: Oxford.

King M, Thornhill C. 2003. ‘Will the Real NiklasLuhrnanrt Stand Up, Please.‘ A Reply to JohnMingers. The Sociological Review 51(2): 276—285.

Syst. Res. 29, 342—367 (2012)DOl: 10.1002/sres



Krause D. 2001. Luhinann-Lecikon. 3rd Edition. Lucius& Lucius: Stuttgart.

Kuhn TS. 1996. The Structure of Scientfic Revolutions. 3rdEdition. University of Chicago Press: Chicago, EL.

Luhmann N. 1995. Social Systems. Stanford UniversityPress: Stanford, CA.

Lulunann N. 1997. Die Gesellschaft der Gesellschaft.Suhrkamp: Frankfurt a.M.

Luhmann N. 2003. The Autopoiesis of Social Systems.In: Midgley G (Ed.) Systems Thinking. Vol 3. SagePublications: London; 65—79.

Maturana HR. Varela FJ. 1980. Autopoiesis and Cognition. Dordrecht: Holland, Reidel; 59—134.

Maturana HR, Varela FJ. 2009. Der Baum der Erkenntnis.Die biologischen Wurzeln menschlichen Erkennens. 2ndEdition. Fischer: Frankfurt a. M.

Miller JG. 1978. Living Systems. McGraw-Hill: NewYork, NY.

Ivlingers J. 1995. Sef-Producing Systems - Implications andApplications ofAutopoiesis. Plenum Press: New York, NY

Mingers J. 2002. Can Social Systems be Autopoietic?Assessirig Luhmann‘s Social Theory. The SociologicalReview 50(2): 278—99.

Morgan G. 1997. linages of Organization, 2nd Edition.Sage Publications: Thousand Oaks.

Nelson RR, Winter SG. 1982. An Evolutionary Theoryof Econoinic Change. Harvard University Press:Cambridge MA.

Parnas DL. 2007. Stop the Numbers Garne. CountingPapers Slows the Rate of Scientific Progress. Coinmunications ofthe ACM 50(11): 19—21.

Pettigrew AM, Whipp R. 1991. Managing Change forCompetitive 5 uccess. Blackwell Publishing: Oxford.

Pistorius CWI, Utterback JM. 1997. Multi-Mode Interaction among Technologies. Research Polici 26(1): 67—84.

Poole MS, Van de Ven AH. 2004. Iheories of Organizational Change and Innovation Processes. In: PooleMS, Van de Ven AH (Eds.) Handbook ofOrganizationalChange and Innovation. Oxford University Press:Oxford; 374—394.

Prigogine 1. 1976. Order through Fluctuation:Self-Organization and Social System. In: Jantsch E,Waddington CH (Eds.) Evolution and Consciousness:Human Systems in Transition. Addison-Wesley:Amsterdam: 93—133.

Richardson GP. 2011. Reflections on the Foundations ofSystem Dynamics. System Dynamics Review 27(3):219—243.

Sastry MA. 1997. Problems and Paradoxes in a Model ofPunctuated Organizational Change. AdministrativeScience Quarterly 42(2): 237—275.

Schwaninger M. 2006. Design for Viable Organizations: the Diagnostic Power of the Viable SystemModel. Kybernetes 35(7/8): 955—966.

Schwaninger M. 2009. Intelligent Organizations: PowefttlModels für Systemic Management. Second Edition.Springer: Berlin.

Senge PM. 1990. The Ffth Discipline: The Art and Practiceof the Learning Organ ization. Currency & Doubleday:New York, NY

Shannon C, Weaver W. 1949. The Mathematical Theory ofCoinnninication. University of Illinois Press: Urbana,IL.

Starbuck WH. 2010. What Makes a Paper Influentialand Frequently Cited? Journal of Management Studies47(7): 1394—1404.

Sterman JD. 2000. Business Dynamics. Systems Thinking and Modelirig for a Complex World. Irwing/Mc Graw-Hill: Boston, MA.

Sterman JD, Wittenberg J. 1999. Path Dependence, Cornpetition, and Succession in the Dynamics of ScientificRevolution. Organ ization Science 10(3): 322—341.

Thompson E, Lutz A, Cosmelli D. 2005. Neurophenornenology. An Jntroduction for Philosophers. In: Brook A,Akins K. (Eds.) Cognition and the Brain. The Philosophyand Neuroscience Movement. Cambridge UniversityPress: Cambridge, MA; 40-97.

Umpleby 5. 1986. A Social System is an Ecologv ofCompeting Conceptual Systems. Working Paper.January 28, 1986. The George Washington University: Washington DC.

Utterback JM. 1994. Mastering the Dynamics of Innovation: How Companies Can Seize Opportunities in theFace of Technological Change. Harvard Business SchoolPress: Cambridge, MA.

Varela E, Maturana H, Uribe R. 1974. Autopoiesis: TheOrganization of Living Systems, Its Characterization,and a Model. Biosystems 5(4): 187—196.

Von Foerster H. 1984. Observing Systems. SecondEdition. Intersystems Publications: Seaside, CA.

APPENDIX: EQUATIONS OF THE SYSTEM DYNAMICS MODEL

(001) Actual Work Performed INTEG (change actual work performed,0)Units: task

(002) adequacy of current routine relative to organizational environment = WITH LOOKUP (requirements oforganizational environment,([(0,0)-(10,10)],(0,1),(1,0) ))Units: drnnl

(003) allocation change time = 10Units: Day

(Continues)

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. 29, 342—367 (2012)DCI: 1O.1002/sres


Syst. Res. RESEARCH RARER

(004) avg life time = 60Units: Day

(005) benefits of new routine = costs of dissolved work*Dissolved WorkUnits: USD

(006) change actual work performed = generation rate of work not solved by current routine + workcompletion rateUnits: task/Day

(007) change delay time = 4Units: Day

(008) change time to adjust forgetting 5Units: Day

(009) competence gap in current routine = target competence for current routine-Competences in current RoutineUnits: competence unit

(010) competence gap in new routine = target competence for new routine-Competences in new RoutineUnits: competence unit

(011) Competence new routine double = Competences in new Routine*2Units: competence unit

(012) Competences in current Routine = INTEG (learning of current routine-forgeting ep, 1)Units: competence unit

(013) Competences in new Routine = INTEG (learning of new routine + “pilot (un)-learning rate“, 0)Units: competence unit

(014) completion of work by new routine = max(min(effect of reflexivity competence on work rates*resourcesfor new routine*productivity new routine,Work not solved by current Routine/TIME STEP),0)Units: task/Day

(015) completion of work with new paradigm = max(min(resources for current routine*productivity newroutine,Work Remaining/TIME STEP),0)*effect of rel fraction on paradigm changeUnits: task/Day

(016) confidence adjustment time = 10Units: Day

(017) confidence based on competence mtpl =1Units: confidence unit/competence unit

(018) Confidence in current Routine = INTEG (net change of confidence in current routine, indicatedconfidence in current routine)Units: confidence unit

(019) costs of dissolved work = 120Units: USD/task

(020) “costs per competence unit (current routine)“ = 150Units: USD/competence unit

(021) “costs per competence unit (new routine)“ = 150Units: USD/competence unit

(023) dissolution rate = max(Work not solved by current Routine*fractional dissolution rate,0)*(1effect ofreflexivity competence on work rates)Units: task/Day

(024) Dissolved Work = INTEG (dissolution rate-obsolescence rate, 60)Units: task

(025) duration pulse = 60Units: Day

(026) effect of competence in new routine in confidence in current routine = effect of competence in newroutine in confidence in current routine T(Competences in new Routine/maximal competences ofroutine)Units: dmnl

(027) effect of competence in new routine in confidence in current routine T([(0,0)-(1,1)],(0,1),(0.397554,0.925439),(0.70948,0.811404),(0.868502,0.710526),(1,0.6))Units: dmnl

(028) effect of competences on productivity current routine = effect of competences on productivity T(Competences in current Routine/maximal competences of routine)Units: dmnl

(Continues)




(029) effect of competences on productivitv new routine effect of competences on productivitv new routine T(Competences in new Routine/maximal competences of routine)Units: dmnl

(030) effect of competences on productivity new routine T([(0,0)-(1,2)J,(0,0.75),(1,1.25))Units: dmnl

(031) effect of competences on productivity T([(0,0)-(1,2)],(0,0.75),(1,1 .25))Units: dmnl

(032) effect of perceived attractivness of new routine on pilot learning rate = effect of perceived attractivness ofnew routine on pilot learning rate T (perceived relative attractiveness of new routine/referenceperceived relative attractiveness of new routine)Units: dmnl

(033) effect of perceived attractivness of new routine on pilot learning rate T

Units: dmnl(034) effect of reflexivity competence on perception bias = 1-reflexivity competence*reflexivity competence

mtplUnits: dmnl

(035) effect of reflexivity competence on work rates delayl(reflexivity competence*reflexivity competencemtpl,change dely atime)Units: dmnl

(036) effect of rel fraction on paradigm change = effect of rel fraction on paradigm change T(relative fraction ofcompetences in new routine)Units: dmnl

(037) effect of rel fraction on paradigm change T([(0,0)-(1,1)],(0,0),(1,1))Units: dmnl

(038) effect of schedule pressure on resources for current routine = effect of schedule pressure on resources forcurrent routine T(schedule pressure)Units: dninl

(039) effect of schedule pressure on resources for current routine T([(0,0)-(2,2)j,(0,0.5),(1,1),(2,1.5))Units: dmnl

(040) external reflexivity competence = 100*pulse(start time pulse, duration pulse)Units: competence unit

(042) forgeting ep = Competences in current Routine/forgetting timeUnits: competence unit/Day

(043) forgetting time smooth(if then else(Competences in new Routine> threshold for forgetting, forgeffingtime when old,le + 006),change time to adjust forgetting)Units: Day

(044) forgetting time when old = 30Units: Day

(045) fraction of tasks correct and complete = 0.6Units: dmnl

(046) fractional dissolution rate = 0.3Units: 1/Day

(047) generation rate of work not solved by current routine max(min(resouices for currentroutine*productivity current routine*(1fraction of tasks correct and complete), Work Remaining/TIME STEP),0)Units: task/Day

(048) indicated confidence in current routine = if then else(Switch awareness of external requirements =0,Competences in current Routine*confidence based on competence mtpl*effect of competence in newroutine in confidence in current routine, Competences in current Routine*confidence based oncompetence mtpl*adequacy of current routine relative to organizational environment*effect ofcompetence in new routine in confidence in current routine)Units: confidence unit

(049) mit work not solveable = 3Units: task

(050) mit work remaining = 60Units: task

(Continues)

Copyright © 2012 John Wiley & Sons, Ltd. Syst Res. 29, 342—367 (2012)DOl: 10.1002/sres


L

1Syst. Res. RESEARCH PAPER

(052) investment costs for current routine = max(0,competence gap in current routine*hlcosts per competenceunit (current routine)“)Units: IJSD

(053) investinent costs for new routine = competence gap in new routine*ulcosts per competence unit (new routine)“Units: USD

(054) leaming of current routine work completion rate*marginal learning effect current routine*0.5Units: competence unit/Day

(055) learning of new routine = completion of work by new routine*marginal learning effect newroutine*normal marginal learningUnits: cornpetence unit/Day

(056) marginal learning effect current routine = WITH LOOKUP (Competences in current Routine, ([(0,0)(100,0.3)J,(0,0.25),(29.3578,0.222368), (57.7982,0.164474), (77.9817,0.102632),(90.5199,0.0552632),(100,0) ))Units: competence unit/task

(057) marginal learning effect new routine = WITH LOOKUP (Competences in new Routine, ([(0,0)-(100,2)],(0.611621,1 .74561),(28.1346,1.52632),(54.7401,1.14912),(75.5352,0.736842),(89.6024,0.359649),(100,0) ))Units: competence unit/task

(058) maximal competences of routine = 100Units: USD

(059) multiplication of efforts to solve unsolveable work = 2Units: dmnl

(060) net change of confidence in current routine = (indicated confidence in current routine-Confidence incurrent Routine) / confidence adjustment timeUnits: corifidence unit/Day

(061) normal allocation of resources to current routine = 0.6Units: dmnl

(062) normal marginal learning = 0.19Units: dmnl

(063) normal pilot learning rate = 0.25Units: dmnl

(064) normal productivity = 2Units: task/resource /Day

(065) normal productivity new routine = 2Units: task/resource/Day

(066) ohsolescence rate = Dissolved Work/avg life timeUnits: task/Day

(067) perceived benefits of new routine =benefits of new routine/(1 + perception bias*effect of reflexivitvcompetence on perception bias)Units: USD

(068) perceived relative attractiveness of new routine perceived benefits of new routine-perceived relativeinvestment costs for new routineUnits: USD

(069) perceived relative investment costs for new routine relative investments costs for new routine*(1 + perception bias*effect of reflexivity competence on perception bias)Units: USD

(070) perception bias = perception bias T(Confidence in current Routine/reference confidence in currentroutine)Units: dmnl

(071) perception bias T([(0,-2)-(3,3)],(0,-0.5),(1,0),(2.5,0.5))Units: dmnl

(072) “pilot (un)-learning rate“ = max(min(pilot learning rate*effect of perceived attractiveness of new routineon pilot learning rate, Competences in new Routine! TIME STEP),-Competences in new Routine/ TIMESTEP)*normal pilot learning rateUnits: competence unit/Day

(073) pilot learning rate = WITH LOOKUP (Competences in new Routine, ([(0,0)-(100,4)J,(0,4),(8.25688,3.07018),(25.9939,1 .92982),(49.5413,0.964912 )‚(75.2294,0.122807),(100,0) ))Units: competence unit/Day

(Continues)


1


RESEARCH PAPER Syst Res.

(074) productivity current routine = if then else(Switch productivity = 0,normal productivity, normalproductivity *effect of competences on productivity current routine)Units: task/resource/Day

(075) productivity new routine = if then else(Switch productivity new routine 0,normal productivity newroutine, normal productivity new routine*effect of competences on productivity new routine)Units: task/ resource / Day

(076) “re-interpretation rate“ = max(0,Work not solved by current Routine*(1tolerable fraction of unsolvedwork-fractional dissolution rate))*(1effect of reflexivity competence on work rate)Units: task/Day

(077) reference confidence in current routine =40Units: confidence unit

(078) reference perceived relative attractiveness of new routine = 6000Units: USD

(079) reflexivity competence = min(external reflexivity competence + reflexivity competences based on newroutine, 100)Units: competence unit

(080) reflexivity competence mtpl = 0.01Units: 1 /competence unit

(081) reflexivity competences based on new routine = reflexivity competences based on new routine T(Competences in new Routine)Units: competence unit

(082) reflexivity competences based on new routine T([(0,0)-(100,100)],(0,0),(100,100))Units: competence unit

(083) relative fraction of competences in new routine = Competences in new Routine/Competences in currentRoutineUnits: dmnl

(084) relative investments costs for new routine = investment costs for new routine-investment costs forcurrent routineUnits: USD

(085) requirements of organizational environrnent = WITH LOOKUP (Time, ([(0,0)-(180,10)1,(0,0.2),(181.101,1.40351) ))Units: dmnl

(086) resources for current routine = delayl (if then else(Switch schedule pressure = 0,total resourcesavailable*normal allocation of resources to current routine, total resources available*normal allocationof resources to current routine*effect of schedule pressure on resources for current routine), allocationchange time)Units: resource

(087) resources for new routine = total resources available-resources for current routine-“resources required fordissolution and re-interpretation“Units: resource

(088) “resources required for dissolution and re-interpretation“ = (dissolution rate + “re-interpretation rate“)!productivity current routineUnits: resource

(090) schedule pressure = Work Remaining/init work remainingUnits: dmnl

(092) start time pulse = 150Units: Day

(093) State of the System = max(Competences in current Routine, Competence new routine double)Units: competence unit

(094) Switch awareness of extemal requirements =0Units: dmnl

(095) Switch productivity =1Units: dmnl

(096) Switch productivity new routine =1Units: drnnl

(097) Switch schedule pressure = 1Units: dmnl

(Continues)




(098) target competence for current routine 75Units: competence unit

(099) target competence for new routine 75Units: competence unit

(100) task generation rate RANDOM NORMAL(0, 10, 5, 1, 1)Units: task/Day

(101) threshold for forgetting 80Units: competence unit

(102) TIME STEP=0.125Units: Day

(103) tolerable fraction of unsolved work = 0.3Units: 1/Day

(104) total resources available = 6Units: resource

(105) Work Completed INTEG (completion of work by new routine + completion of work with newparadigm + work completion rate, 0)Units: task

(106) work completion rate max(min(resources for current routine*productivity current routine*fraction oftasks correct and complete, Work Remaining/TIME STEP),0)*(1effect of rel fraction on paradigmchange)Units: task/Day

(107) Work not solved by current Routine = INTEG (generation rate of work not solved by current routinecompletion of work by new routine-dissolution rate-“re-iriterpretation rate“, mit work not solveable)Units: task

(108) Work Remaining = INTEG (multiplication of efforts to solve imsolveable work*reinterpretationrate“ + task generation rate-generation rate of work not solved by current routine-work completionrate-completion of work with new paradigm, mit work remaining)Units: task



Documents

Syst. Res. 29, 342—367 (2012) Library Closure a… · Systems Research and Behavioral Science Syst. Res. 29, 342—367 (2012) Published online 24 February 2012 in Wiley Online Library