A NEW MODEL OF STRATEGY APPLIED TO THE RUSSIAN SITUATIONi Robin Matthews Professor of International Business Kingston University UK

INTRODUCTION Perhaps for the first time in history a single system of economic and business organization dominates the planet: the market system or capitalism. It cannot be understood in traditional terms. Capitalism changed profoundly in the 1970’sii. The principles that underlie the change are information, globalization, and financial deregulation. Insights into management in the new era are provided by theories of complexity and strategic games, and they form the basis of the strategic framework that is describediii. In the new era of capitalism, information and knowledge are the dominant sources of the competitive advantage of firms, and the competitiveness of nations. In many ways the world economy has become globaliv. Financial capital and information, to a large extent beyond the control of national governments, flow across national boundaries. The crisis facing the Russian economy from the 1970’s onwards resulted from the failure of the Russian form of industrialization to adapt. The interaction of globalization, international finance, and information technology, together with changes in the rules of the game in the cold war, especially the introduction of Star Wars by the Reagan administration in the USA, meant that the outmoded Russian management system was no longer insulated from competition. The focus of the paper is on three things: i. the nature of strategy, ii. the description of a general or meta model which managers can use to develop their own models suited to the particular circumstances they have to deal with, iii. application to the Russian situation. Strategy is the alignment of the objectives of an organization with its capabilities. It is a means of realizing the potential in society: system states and control parameters are two important concepts in relation to this. Strategies are trajectories through time: in strategic decisions a path or trajectory from one system state to another is chosen, A set of control parameters limit the time paths that can chosen. Metaphorically system states describe the current arrangement of pieces on a chessboard; control parameters correspond to the rules of the game. These rules determined by external and internal factors. External factors originate in the business environment. Internal factors include formal mechanisms such as rules, hierarchies and procedures: informal elements include, the culture norms and values of the organization. Control parameters determine the strategic trajectories over timev. Since they originate partly within organizations, control parameters of the future can be affected by contemporary decisions: in contrast to rules in games of chess, which are more or less immutable. Rules of the game differ according to the region and the era in which it is played. Managers conditioned by the habits of a planning economy find it difficult to

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distinguish strategy and optimization: the distinction is discussed. Ideas in the paper apply not only to commercial businesses, but also to the strategies of national governments and institutions. Secondly the paper sets out a general model or meta model, that can be used by managers to develop their own models of strategy. These particular models must be tailored to the system states or special conditions of time and place in which they are required to operate. Everywhere managers consciously or not, use models to understand their organizations. The variables contained in the models they use do not differ. It is system states and control parameters that differ. System states encompass the psychology of the players, which is partly historically determined. An added complexity is that system states are known only imperfectly. Managers develop models, which select certain variables as important, and treat other aspects as relatively unimportant. The role of strategy theory is to help manages formulate such models. Rectifying the problems of Russian management is not merely a question of adopting particular formulae. Techniques must be adapted to the relevant system state: and control parameters, the circumstances that constrain future possibilities. This brings us to third concern of the paper, application and prescription to Russia: issues that should be approached modestly by a foreigner. In partial exoneration, it is offered as an antidote to some of the advice fostered upon managers by consultants from abroad, and monetarists at home. One of the scientific paradigms of the paper is complexity. Prescriptions should be seen in this light: more like the meditations of Tolstoy's Kutozov, than instructions in a motor repair manual. Past performance Before castigating Soviet management, its successes should be rememberedvi. We should also recollect the enormous cost at which success was bought: ruining the lives of many people, and deforming the economy and the ecology. These aspects, which relate to the ontological dimension of the meta model outlined later in the paper, were ignored. Totalitarian Marxism failed, but not all it brought about was bad. For long periods Soviet GNP grew faster than most of the world, even when the falsifications of Soviet statistics are discounted. Until the late 1960’s there is no substantial evidence that Russia lagged behind the West technologically. Countries of the former Soviet Empire inherited standards of health, literacy, and scientific education, far beyond those of developing economies elsewhere. Adopting the lower range of estimates, average annual growth in the period 1928-40 was 3.2 per cent, between 1950-60 it was 7.2 percent, 1960-65, 4.4 percent, between 1965-70, 4.1 percent, and 3.2 percent in 1970-75. Thus, even in the first ten years of the Breznev era, there was moderate growth. Huge human and environmental costs were the price of this. In other words, key stakeholders were ignored in the drive to increase the military and ideological power of the state. After 1975 though, stagnation set in. Growth was negative in 1980-82, and in 1987. For the most part has been negative since then. According to the official data 1997 was a year of achievement for the virtual economy. For the first time since 1992, the economy grew. The current account of the balance of payments was in surplus. Inflation declined and the rouble appeared stable. Unresolved and fundamental issues existed in the real economy lurking behind false

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accounting. The crisis of 1998 revealed the inadequacies of Russian economic development. But it was the trigger, rather than the fundamental cause. As a result of the transition in capitalism that began in the 1970’s, the scope of competition widened and Russian firms could no longer be insulated from international competition. New organizational structures became necessary: structures capable of learning and adapting rapidly to technological change and shorter product cycles. Customers became more significant stakeholders. Competition from emerging economies, especially in South East Asia became intense. The reasons for Soviet economic failure are well documented, and need only be sketched here. By the mid 1970's diminishing returns had set in to the method of accumulation by squeezing agriculture of resources, and harvests, to subsidize industry, supplement the urban workforce, and feed the cities. Growth in aggregate production requires growth of both labour and capital. Inevitably however, the rate of growth of the industrial labour force slowed down and investment, innovation, and growth in the productivity of capital were insufficient to compensate for this. Important sources of demand, which might have sparked productivity increases in the emerging industries of the late twentieth century, were choked off. Heavy industry was emphasized. Consumer goods, housing and services were forsaken to provide capital goods for the military industrial complex. Focus on natural resources meant that the rouble became a petro currency. Added to these things, the toll of military competition with the USA, the richest economy in the world in material terms, and the higher stakes demanded by the Cold War under the Reagan administration in the 1980’s threatened to drain Russia. The events of August 1998 were the trigger for the Russian crisis at the end of the decade. The fundamental causes lie in low productivity and management failures. Russian management techniques inherited in the 1990’s were geared to the early, not the late twentieth century. Vertically integrated industrial structures appropriate to an earlier stage of development were unable to adapt to the new era of capitalism. Things were made worse by the adoption of naive monetarism. Reformers, if they considered them at all, assumed that the institutions necessary for capitalism would emerge spontaneously, like Phoenix from the ashes of the old Soviet system, in response to market reforms, and monetarist policies. To assume this can happen is to ignore the system state in Russia, and to compound rather than resolve problems. Whilst general principles of management and economics are important, they need to be tailored to the system state if they are to result in feasible policies. In the light of these observations, a principal aim of the paper is to describe a meta model, which is invariant with respect to time and place, and which can be adapted appropriately by managers. Particular models are necessarily simplifications of some more general model. The meta model provides a framework for developing strategy that focuses on key variables. It is general enough to enable managers to consider the sensitivity of conclusions to variables and interconnections that have been omitted for the purpose of simplification. The meta model is composed of three sets of variables: decisions, value adding activities, and the business environment. These variables interact in a domain that includes many different levels of human experience, which is termed an ontological domain for the purposes of exposition. At a practical level, the meta model is based upon experience of working with international firms. The scientific

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paradigm is interdisciplinary, drawing upon theories of complexity and of games. We turn to these theories in the next section. COMPLEXITY AND GAMESvii Organizations can perhaps best be understood as complex systems: because they involve coalitions and interdependent behaviour, game theory also provides insights into their strategies. Organizations encompass large numbers of interacting variables. They are non-linear: the whole amounts to more than the sum of the individual parts because of increasing returns. Possibilities exist for the emergence of new capabilities. Complex systems are sometimes described as non-linear adaptive networks. The global businesses environment, the central nervous system, ecologies, the immune system, evolutionary genetics, are examples of adaptive non-linear networks. They are characterized by • intense interactions among large numbers of activities and agents or decisionmakers. • bounded rationalityviii. • uncertainty and limited information • learning and adaptation. • non linearity, increasing returns, scale and scope economies. • speculation and anticipation. In the new era of capitalism, industries and niches emerge in which successful technology creates a web of supporting industries. This brings us to a second theoretical concept, games. As in game theoretic models, players in the global economy build models of others behavior, and use them to make predictions. Models are rarely descriptive: usually they are prescriptive, recommending certain courses of action. The central tenets of game theory are that outcomes are the result of interdependent decisions, and that players anticipate each other moves. With these ideas in mind it is natural to partition strategy as follows: • system-states that reflect the current environment, past strategies, and determine what it is possible to achieve in the future, • agents or decision-makers, and their preferences, • strategic decisions attempting to transform one system state into another, • control parameters that govern the way strategies can transform system states over time. Networks Complex systems can be understood as networksix. Networks are made up of interconnected nodes. The connections are more important than the nodes themselves. The value of the interconnections gives rise to non-linearities. A network is illustrated in Figure 1. It captures the essentials of complex systems, and some aspects of game theory. The nodes are connected, reflecting interactions and interdependence. The value of the system as a whole includes i. the value of the nodes, and ii. the value or impact of the linkages, reflecting non-linearity of complex systems. Realizing potential value depends on the nature of the game and on co-operation: this can be seen as coalition behaviour in a series of co-operative games over time. As Figure 1,

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shows many linkages exist, giving rise to uncertainty about outcomes, and possibilities for the emergence of new opportunities, for decay, and for chaos. The idea of a network appears in a number of ways in the paper. The global business environment in the new era of capitalism is a network of interacting variables. Organizations have adapted to this by forming networks of relationships, internally and externally. The meta model outlined in the next section can be viewed as a network of interacting variables; the role of the strategist being to decide which variables (nodes) and which linkages are significant. A META MODEL Some observations on terminology are necessary. Linking game theory to policy means that terms such as strategist, policy maker, decision-maker, player, or agent are used interchangeably in the paper. The same applies to organization, or firm, since the principles apply equally to publicly and privately owned corporations, to profit and not for profit institutions; government departments, welfare agencies, and so on. These equivalencies follow from the complex interaction between financial capital, technology, demography, and politics in the new era. The mobility of capital, irrespective of national boundaries, means that financial capitalists continually seek higher returns on their investments. Ageing populations in Western Europe and North America, and the rising cost of medical treatment, mean that pressures for higher social spending coexist with reluctance of their electorates to vote for tax increases. So the drive to achieve ever higher returns and greater efficiently commits both public and private sectors to competitive forces. The surplus The purpose of organisations is to create a surplus, maintain it against competition, and distribute it among stakeholders. Without a surplus, societies cannot grow. The surplus can be measured in monetary, or psychic terms. It can be expressed in a great number of ways financially; profit, return on capital, return on equity, sales, earnings per share, dividends and so on. It also takes non-monetary forms: good lives, security, care for the ecology, leisure, or an exceptional product. In other words, the surplus may be distributed to owners, customers, managers, or to the community in general. The game theoretic term, payoff (with the connotation of transferable utility), is used interchangeably with surplus. The capitalist system incentivizes firms to play both positive and negative sum games. Learning and creating new sources of competitive advantage through new products and processes are positive sum games. Raising barriers to new competition are zero or negative sum games that require a regulatory framework to curb them. In positive sum games players compete for a greater share of the surplus created by the capitalist system brought about by financial and industrial capital, innovation, and the globalization of businesses seeking ever cheaper resources and bigger markets. The process is Darwinian, in the sense that inefficient traits are deselected by bankruptcy or the threat of bankruptcy: competitiveness is reinforced by a Lamarckian process according to which discovering new sources of competitive advantage becomes an acquired characteristic. Such characteristics are known as core competencies, or emphasising the need to adapt, dynamic capabilitiesx.

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Failings of Russian management are rooted in a social system, which traps many of them in zero, or negative sum games. In the old Soviet system, the surplus created by society was appropriated by politicians, who used it mainly for two purposes: ideological influence and military power. The new system lacks a regulatory framework, which can combat barriers to competition effectively. Also the heritage of the old system, under which markets were quasi-legal fringe activities, naturally forged a link between economic activity and criminal behaviour. The naivety of early reformers and their advisers can be seen with the benefit of hindsight: perhaps greater humility in their expectations of their market reforms would have moderated some of the current problems. The theory of the determination of the surplus created by organizations is formed out of four building blocks, • Ontology • Decision variables, • Activity variables, • Environmental variables. Ontologyxi The importance of linkages and networks of relationships means that management has to be distributed and decentralized. The set of managers probably extends to everyone involved in the creation and distribution of the surplus. Property owners, customers, financiers, contractors, creditors, government, the community, the employed and unemployed, the dispossessed, the criminal, as well as chairmen of important committees, and eminent patrons of art or economic development, all in their different ways, take part in the process. Perhaps the most fundamental hypothesis of the paper is ontological: the need to recognize the legitimacy of different levels of experience or of being. Three ontological issues are relevant to the construction of a Meta model: i. distribution of the surplus created by society among its members, ii. realisation of new opportunities through innovation and creativity, iii. the ecology. The issue of distribution involves values or ethics. Ontologically this represents the exercise of freedom by an individual to acknowledge the being or existence of others. To survive and grow, human organization must create a surplus over immediate needs and wants. The new era of capitalism means that in all societies many people have become marginalized, and gains from economic growth have gone to the few. An ethical question arises as to how this surplus should be distributed. The possibility of inequality is a necessary condition for providing incentives in a market economy. As Keynesxii pointed out, too much inequality is both dysfunctional and unjustified. Hence he suggested a compromise. To preserve the incentives provided by the possibility of obtaining a bigger share of the surplus in society, he advocated running economies at sufficiently high levels of aggregate demand to guarantee full employment. He saw creation of demand by government spending and budget deficits, at appropriate points on the business cycle, as a necessary condition: a set of pragmatic solutions that are the consequences of acknowledging self existing in time, in relation to others. Rmatthewsanewmodel15/05/0317:56

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The second issue, of creativity, originates in the world of imagination: the recognition of the existence of the existence of a perhaps timeless world of potential that is there to be discovered and may be actualized in time: a world that always is accessible to the imagination but may or may not be feasible or capable of actualization in time. Unfortunately imagination has been downgraded to fantasy, as a result of misinterpretation and corruption of scientific method. Imagination derives from magical image (imago magia), and is the basis for many things including marvellous modern technology. Innovation, exploring and exploiting new technological possibilities, or the potential for new markets products, or innovations in management and organization, emanate from the world of imagination, a world of being in its own right. Creativity consists of expressing objects of imagination in the world of ordinary experience. Scientific progress, research and innovation unveil deeper and perhaps richer layers of potentiality. On some interpretationsxiii, what is revealed at each successive stage of scientific enquiry, is merely a series of veils, in never ending succession, behind which is an unknowable essence. The danger is that the veils become seductive forms: consumerism, materialism, ideology, and one form of idolatry or another. The third issue, of ecologies becomes ever more critical. All productive activities that go into creating a surplus involve transactions with the environment. Essentially low entropy in the form of useful resources is extracted, and as a result of production and consumption, high entropy or waste is deposited. This is simply an expression of the second law of thermodynamics. The process is irreversible. The increasing entropy of closed systems gives a direction to time. When populations are small, and growth meagre, the environment may be capable of absorbing pollution of the world’s oceans, rivers, landscapes, and surrounding atmosphere. As growth accelerates, and expectations expand, this becomes increasingly implausible. Modern capitalism and old communism are alike in modelling the ecology as an inanimate source to be exploited, without status as a being, and in ignoring the interdependence and coevolution of economies, societies, with ecologies. The three issues are part of the ontology of organizational strategy that should be considered. Although they affect the empirical world profoundly, they emerge from a realm beyond that of immediate sensory perception and empirical verification (or falsification) by reference to facts and data. A meta model, if it is to be useful in the ways described above, should include them. Activity variables Activities are the building blocks of system states. They are the immediate targets of decision variables. One of the first tasks in strategy is to decide which are the relevant value adding activities. Typically there are many such activities and the relevant definition of activity depends on the nature of the strategic problem. In a merger or alliance it is the entire organization. It may be a nation state or business unit, value chain, or a process, a team, or even, in some cases an individual partitioning his or her time. In fractal geometry this replication at many levels, is known as self-similarity. Activities have a fractal structure and dimension. They have a similar structure, that of a network of interrelationships no matter on what scale they are magnifiedxiv.

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Organizations can be thought of as networks or coalitions of activities whose boundaries shift as they grow, decline, or restructure. Activities are formed into coalitions or networks in order to capture the potential payoffs that result from linking them. Coalition formation takes place at many overlapping levels, within organizations, and between them: alliances, and mergers between firms, coalitions between divisions, functional areas, businesses, projects and teams. Defining activities is not a simple task. Activities and networks are discrete only in an artificial sense. An organization's supply chain consists of a network of relations or value chains which overlap activities and may cross the boundaries of business units or nations, so the measure of its extent depends on the length scale chosen. As we magnify the perspective, their overlap gives them a fractal dimension since levels are not discrete; alliances at the firm level require interactions at the team level, for example. Looking inwards from the level of merger or alliances between firms, to team working, within them, reveals self similarity, in that value creating networks exist within networks, and within them, further networks exist, and so on. This accounts for the complexity of defining value-adding activities. Given the perspective of organisations in the last few paragraphs, they can be seen as coalitions of N activities. Payoffs are created; individually, as single member coalitions (nodes), and interdependently as two or more member coalitions that generate synergies. Interdependence is simplified by viewing agents as producing joint outputs, those that have value in themselves, and those which create value in others reciprocally: the yin and yang of business synergy. The value of interdependence or synergy is given by the difference between the sum of the values of assets in isolation, and the value of assets as part of the organizational network A key decision about activities is how big the network of interconnections should be. Such questions involve the size of organizations, which often extend far beyond national boundaries. The hundred largest multinational companies in the world own nearly 2 trillion dollars of assets outside their own countries - a quarter of the worlds stock of foreign domestic investment. Inevitably mergers will make them even bigger.xv Decision variables Strategic decisions attempt to steer organizations from one system state to another. They take place within the confines of control parameters. Control parameters act like a transport system that an organization must travel on, but which in the long term can be extended, revised, removed, restored, or destroyed by decisions. Decision variables reflect expected utilities or preferences: they encompass the ontological issues referred to earlier in the section. Since organizations are thought of as coalitions of activities, realization of potential payoffs depends not only on recognition of payoffs, but also on cooperative behaviour in a network of relationships. Reinterpreting Figure 1, potential gains from linking activities may exist, but cooperation is required to realize themxvi. So the norms of group behaviour are important. Three types of utility are relevant to these observations xvii • instrumental, • conditional

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• symbolic In each case it is expected utility that is important. There are no facts here that are independent of expectations. Actions and reactions are based on the interpretation and anticipation of system states, which are what they are perceived to be. When motivated entirely by expected instrumental utility, decision-makers take no account of the impact of their decisions upon others. Other people's decisions and actions are considered to be entirely independent. Decisions motivated by expected conditional utilities take account of the impact upon others. Decision makers consider that their altruistic or cooperative behaviour will be reciprocated, and their selfish or opportunistic behaviour will be reflected by selfishness on the part of others: so in many games players adopt tit for tat strategies, assuming the best behaviour by others, and acting co-operatively or unselfishly until the assumption is contradicted. Symbolic utilities arise when the probable outcome of an action is associated with another outcome to which the individual attaches utility. A parallel exists between spin glass systems of statistical mechanics and decisionmaking. Treating spins as binary decisions in a co-operative game, agreement to cooperate or decisions not to do so, are like magnetic fields the can align or not. The spin glass is a confection of positive and negative feed backs occurring as each of the magnetic atoms in the glass tries to align its associated magnet with neighbours. Frustration occurs because of conflict and competition among the interaction of spinsxviii. Given purely instrumental utilities, realization of payoffs in a spin glass situation, becomes a random process, dependent on the chance alignment of spins or decisionsxix. The initial system state together with random decisions may lock an economy into a new system state that may or may not be optimal but from which it is difficult to emerge. This describes a variety of real world situations in Russia and elsewhere. Thus for example economic development may be much more the result of random processes than we care to acknowledge, and so may be the case with suboptimal situations. Thus becoming locked in negative sum games in the form of non payment of taxes, vandalism of exhaustible resources, senior managers and officials running apparently legitimate business which have with close relationships with mafiya, and profiteering from drugs and arms, may be symptoms of chance. The problem for Russia is that potential payoffs exist, but appropriate control mechanisms enabling a transition to take place between one system state and another, do not. Formal control parameters such as laws, regulations are one avenue limiting the damage. The assumption of post perestroica reforms was either that such control mechanisms existed or would emerge spontaneously once the incentive mechanisms of the market were put in place. Incentive systems with monetary penalties and rewards are another: but as Leonid Hurwicz pointed out foolproof financial incentive mechanisms just do not existxx. Much of management skill consists of designing organizational activities in such a way that positive sum games exist, then generating the conditional and symbolic utilities necessary to cooperation and non opportunistic behavior. In the new era of capitalism, organizations form networks of relationships in their attempt to achieve competitive advantage. This has transformed the nature of management: it now involves managing networks of relationships that are often informal, and over which they have no hierarchical authority. Informal control parameters, such as culture,

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mission, shared vision and trust have become critical in the attempt to manage network organizations. Attempts to manipulate corporate culture reflect efforts to create conditional expected utilities conducive to the creation of quality, trust, and synergy. Symbolic utility is often summarized in mission and vision statements, link corporate goals to personal objectives valued by individuals. Relating these observations to Russia, there is a plus and minus side. Evidence is that decision-makers at important nodes in Russian institutions act on the basis of instrumental utility, imposing huge costs on society. As new networks are formed decisions far from the central nodes becomes increasingly significant, and these need to be managed by the informal control mechanisms associated with conditional and symbolic utilities. Hence poor or corrupt decision making at the Centre exercises less influence, and new system states and control parameters can evolve. But there is also a negative side. The problem of creating such informal control parameters is that the evidence is that many Russian managers see market processes as zero or negative sum games. So evolution is limited by variables in the business environment. Environmental variables Whereas decision and activity variables exist within organizations and can be influenced by them, environmental variables are external to the extent that people form expectations about them. Environmental variables can be divided into three sets; i. expectations about the current system state, and anticipations of what is feasible given the system state, ii. history or path dependence, and iii. stochastic, random, or unexpected events. The three elements are connected. Expectations can become selfreinforcing in that the prevalence of an event, or beliefs about it, can influence beliefs about its prevalence in the future. In this way lock inxxi effects may occur. One technology may become dominant over another simply because a critical mass of people use it. Such was the case when VHS technology that became the standard rather than Betamax; or when loss of confidence in a currency or an asset triggers a financial crisis. Random events at the outset can favour one outcome over another and generate a self-reinforcing process in which that outcome becomes dominant. As a firm gains market share, or the international ranking of an economy rises, learning effects occur that facilitate improvements in costs, productivity, quality and competitiveness generally. So markets become locked in to the products of particular firms or nations. Expectations about the system state relate to a multitude of aspects, including, competitive dynamics, the behaviour of rivals and collaborators, macroeconomic variables (interest rates, taxes, exchange rates and so on), and political, social and demographic factors. History is an irreversible factor reflecting the path or trajectory an organization has followed in the past. Where an organization has come from (its trajectory), the culture, shared values, reputation, market share, that has been inherited, all influence both the current system state and its future trajectory. The sequence in which decisions are made influences their eventual outcome, because the current system state determines the probability of the next one in the sequence. Thus random influences play on strategy. Crises are often stochastic and unanticipated, even when, in retrospect, the signals are clear. Events and beliefs become self-reinforcing, causing positive feedback that magnifies disturbance. The

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crisis of 1998 emanated from bank failures, and collapse of overvalued real estate, and equity prices in the emerging nations of South East Asia. The emergence of China, accompanied by successive devaluation of the yuan, aggravated the situation, upsetting the previous balance, as China asserted herself as an economic power. Many aspects of South Asian economies, especially the close relationships between governments, industry, and banking, previously heralded as sources of superior performance, are now seen as seeds of distress because they legitimized and encouraged overexposure to risk in the financial system. Temporarily Asian economies descended into chaos, and international capital flowed into emerging economies like Russiaxxii. The critical dependence of the Russian economy on the oil price, that, with hindsight, was bound to collapse as demand for oil fell after the Asian crisis, went unregarded. The debt burden forced the government to reschedule payments. There followed destabilizing flights of capital that led to a severe crisis and hardship: but chaos was not total but confined within the limits of an attractorxxiii. The relatively low dependence of Europe and North America to trade with South East Asia together with the prosperity of the USA prevented the crisis spreading to Western Europe. The problem of contagion arose from the confusion between free trade in goods and free trade in financial assets. The case for deregulating trade is that trade in goods and services between nations is potentially a positive sum game, if tariffs and other barriers do not hinder it. The problem of extending deregulation to financial assets is that these are subject to expectations and anticipations that can become selfreinforcing, causing positive feedback, and mayhem. The issue of positive feedbacks is discussed later, but the simple fact relevant to global financial mobility is that it took many generations to find adequate means of regulating financial systems in developed economies. So emerging and transition economies cannot achieve this over night: they are not part of the system state of these economies. As yet, no effective system exists for supervising and regulating financial flows internationally either. Modelling strategy Figure 2 illustrates the relationship between activity (A), decision (D), and environmental variables (E). Ontological considerations outlined at the beginning of the section form the their setting. Particular models might focus exclusively on one set of strategic variables, (A), (D), or (E). Alternatively variables may be chosen from all three sets (G). Combinations of activity and environmental (J), activity and decision (H), environmental and decision (F) variables may be selected. The critical question is how sensitive particular models are to variables that have been excluded. The effectiveness of strategy is determined not only by relationships between the sets of strategic variables, but also by qualitative issues of value, creativity, and ecology. Control parameters Control parameters i. set limits upon the paths that an organization can follow, and ii. are themselves determined by decisions. Strategic decisions transform one system state to another via trajectories determined by control parameters. System states therefore reflect control parameters, which include:

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•

Market structures, competition and the laws, rules, regulations, set by governments that control the behaviour of institutions. • Formal mechanisms, existing within organizations: rules hierarchies, procedures, structures, and architectures that exist within organizations. • Informal mechanisms, within organizations: mission, vision, culture, and norms of behaviour. • Scientific knowledge, the state of learning and information and the way it is shared throughout society. The degree of influence of decisions depends very much on the basin of attraction activities are caught in. In stable environments with stable attractors their influence is smaller, more predictable and the impact of formal mechanisms is relatively greater than in unstable environments with strange attractors. We turn to this in the next section. RUSSIAN MANAGEMENT STRATEGY One of the many ways in which history or path dependence conditions Russian managers is that it is difficult for them, given a heritage of central planning, to distinguish strategy from optimizationxxiv. Yet the two are fundamentally different. Optimization takes the form of attempting to maximize some objective, for example profit or rent, or to minimize cost, subject to a set of constraints. Usually the objective is unambiguous, and the constraints are known. Variables range over a regular surface, so it is appropriate to use differential calculus as a tool. If a solution exists to the (primal) problem of maximization of an objective function subject to a set of constraints, then a set of shadow prices exist to the (dual) problem of achieving given objectives at minimum cost. To achieve a regular or even surface, without holes or gaps or the ruggedness of a mountain range, an assumption of convexity or approximate convexity is adopted to convert the landscape of variables into one which is friendly to the use of differential calculusxxv. In optimisation risk is handled by introducing expected values, and variation, measured by the variance or standard deviation of decision variables. Risk is hedged by diversification, measured by correlation or covariance between variables. Thus in the case of maximization, we have an objective, creating a surplus of benefit over cost (or expected benefit over expected costs). The time stream of (anticipated) profit (the expected difference between revenues and costs) is handled by reducing future benefits and costs to their present value by a discount factor, the cost of capital. The cost of capital is expressed as the weighted average cost of the equity and debt of the firm. Profit can therefore be increased in three ways: raising benefits, cutting costs, or lowering the cost of capital by finding cheaper sources of finance. The distinctiveness of strategy under a market system when compared the idealised theoretical planning systems was discussed by Hayek, von Mises, and others in the 1930's. Essentially idealized mathematical abstracted from the key questions of information costs and incentives which decentralized market systems were able to handle much more effectively than centralized planning systems. Strategic decisionmakers have bounded rationality: limited powers of cognition and calculation. Most important, they are constrained by information or Kolmogorov entropy: the further decision makers look into the future, and the more they shift operations from the

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current (spatial) location, the less useful is current information. This is true of all situations. In strategy there is never sufficient information. The nature of strategy is captured by a metaphor of a complex system. Consider a landscape, or matrix of potential payoffs that are generated by activities as stand alone entities, or as interdependent relationships creating synergies or complementarities. The strategic problem is to realise payoffs, and to distribute them among stakeholders. Bounded rationality and information entropy means that the landscape is unmapped. The aim is to try to reach the highest peak. There are large numbers of possible linkages between activities and many stakeholders, who have different objectives, competing for their share of payoffs: as profit, wages, value for money, ecologically friendly production, ethical investment. The size of the problem increases exponentially with the number of activities and agents or decision-makers consideredxxvi. A complete strategy would specify what to do in every situation, but such completeness can never be realized. Also strategy is adaptive: rivals, competitors, and collaborators respond to each others moves in a complex way, based on their anticipations and expectations. The landscape is rugged or uneven, so the methods of calculus appropriate to standard optimization are inappropriate. To pretend the surface is regular by introducing convexity assumptions is to miss the point. Many of the local peaks may correspond to profitable niches or segments, and sometimes the problem is that organizations are competing in the wrong mountain range, the Alps rather than the Himalayas, for example, issues that are ruled out when the surface is smoothed. When managers choose a strategy they do not consider every alternative, even among those they are aware of. Strategies are chosen if they are considered to improve things or place the organization on a path or trajectory in the direction of its goals. As they get nearer to the target typically they take fewer and fewer risks: this procedure is described as satisficing in contrast to optimizing. Trajectories and attractors Trajectories from one system state to another are determined by strategic decisions but confined within the existing set of control parameters. So control parameters both set limits upon decisions and are determined by them. There are two distinct types of trajectory: T type and K type. Figure 3 illustrates the situation. P(1) is the area of feasible system states and realizable payoffs. P(2) is the system state governing existing payoffs. P(3) is a sea of potential payoffs, which is probably limitless, representing system states and trajectories beyond the horizon. Strategic trajectories T(1), T(2) and T(3) illustrate a set of possible paths into the future that may be achieved as a result of strategic decisions: paths from where the organization is to where decision makers want it to be. T type trajectories represent the transformation of the feasible or realizable, into the actual objects or events: artefacts, products, markets, and innovations in management or organizational structure. Trajectories from the region of actual or feasible region P(2) or P(1), into an entirely new set of options and possibilities P(3), are denoted K(1), K(2), and K(3). K type trajectories are generated by imagination: invention, innovation, and discovery of new knowledge, by individual or collective actions. K type trajectories symbolize from the recognition of new potential payoffs and their transformation into the realm of what is feasible or realizable. Ontologically, both K and T trajectories represent a transformation from one level of being to another. K trajectories are contemplative, or

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imaginal journeys, producing mental images that may be crafted by T type trajectories into created objects or processes. Topologically, region P(1) is an attractorxxvii. Attractors may be periodic or chaotic. They are like containers prescribing patterns of behaviour that may be stable, or chaotic. Stable attractors contain equilibrium points or regular periodic behaviour. Strange or chaotic attractors contain unstable behaviour. Attractors are thought of as basins or vortexes that attract variables to a particular pattern if they are sufficiently close. Trajectories based in periodic attractors have regular paths and patterns over time. They may, for example, behave cyclically like an idealized business cycle, ranging from boom to slump, through downturn and recovery, in a predictable way: an organization’s performance in terms of profit may follow the same cycle. Such may be the situation of organizations in stable environments and with certain markets. Vertical structures, hierarchies, with clearly defined lines of authority, communication, and roles, are appropriate. Alternatively attractors may be strange or chaotic. Two implications of strange attractors are: i. chaos and ii. sensitive dependence upon initial conditions. i. Chaos. Strange attractors are chaotic: the temporal trajectory or path that the system follows from moment to moment is unpredictable, but the pattern is set in the sense that the infinite number of possible trajectories are confined within the strange attractor, or the basin of attraction that surrounds it. ii. Sensitive dependence upon initial conditions (SDIC). Unlike regular systems, strange attractors display immense sensitivity to initial or starting conditions. When it is caught in a strange attractor, the behaviour of a system depends upon the minute details of how it was launched. The implications for the Russian situation are complex. The chaotic aspect of strange attractors provides a good description of the current system state. Russian organizations are caught in strange attractors. Because of a turbulent business environment, politically and economically, the networks adopted by many organizations in the West were appropriate: informal and flexible lines of authority, fluid roles, open lines of communication, and distributed or decentralized decisions. Using the perspective of the meta model, the fractal nature of activities means that this mode of organization must become the norm at many levels: organizations, businesses, projects and teams. This is not feasible in Russia given the current system state of Russian organizations. The mistaken assumption of Shock Therapy was that Russia could be shocked out of her current system state over-night by the adoption of monetary and market reforms: from P(2) to the P(4) which was not feasible given the existing system state and control parameters. The SDIC condition does mean however that the situation is dependent critically on the details of decision making, so that individual managers in Russia can make a difference. This can occur through recognition of existing limitations on T type trajectories, and realizing K type trajectories that expand the scope of system states.

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CONCLUSION A last demand upon the reader's patience is to remind him or her of the three aims set out at the beginning: observations on the nature of strategy, a meta model, and applications to the Russian situation. Strategy is defined as a trajectory over time from one system state to another, governed by an appropriate set of control parameters that are themselves the targets of strategic decision. The goal of strategy is to increase the surplus. This should be seen in relation to the ontological aspects of the model that have been identified: the values and ethics of distribution of the surplus; the creativity required to turn potential into realized payoffs; the ecology which economic systems use to transfer their low entropy, into waste. Variables in the meta model determining payoffs are activities, the targets of strategic decisions, and the business environment. Particular models used by managers are formed out of a subset of these variables in the context of relevant system state and control parameters. A number of applications and observations about the Russian situation are contained in the paper: a further one relates to the failure of post perestroica reforms to take account of existing system states and control parametersxxviii. The market economy and the impacts of monetary policy were seen in idealized terms. In ideal economy non-competitiveness causes falling demand, prices and earnings and rising unemployment. This results in output reductions and either improvement in the efficiency of firms of their elimination: the trajectory over time is a negative feedback system that corrects problems. It may mean that foreign firms dominate the sector or the economy. The Russian economy functions differently. The reasons lie in the system state, and the dual decision taken in the 1990's: to achieve democratic and economic reforms simultaneously, given the lack of appropriate market institutions governing trajectories from one system state to another. Desirable as this may be from some points of view, the dual decision constrains policy options: the levels of bankruptcy, unemployment and additional hardship would be intolerable and infeasible given the existing system state. Hence non-competitiveness is disguised by the virtual economy. Firms declare profits when they are earning none. Governments receive fictitious taxes. Bills of supplying firms are unpaid. Government debt accumulates alongside private sector debt. The gap between government receipts and payments is closed by borrowing. The process is illustrated dramatically by the period leading up to the crisis of 1998. Borrowing to a large extent took the form of issuing GKO’s. As debt accumulated and more and more borrowed funds were required, GKO yields increased. This attracted in foreign speculative funds. The role of financial regulation in an ideal market economy would have been to halt the process by raising the repo rate (the borrowing rate the Central Bank charges the rest of the financial sector via its open market operations). Lack of appropriate institutions and regulations meant that this did not happen. Indebtedness was fed by injections of capital from abroad, which further destabilized the system. Instead of negative feedback cycle, which might have neutralized pressures via higher interest rates, and squeezing of the money supply, a positive feedback cycle arose through the influx of speculative money. The selfreinforcing mechanism continued into crisis and default. The process is typical of chaos and a Russian system state that is part of a strange attractor. The interaction,

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interdependence are characteristic of the complex game taking place within that system state. Putting the process into the perspective provided by Figure 3, the early reforms were a denial of the Russian system state. They represented an attempt to achieve in the short term a T type trajectory from P(2) into P(1)*. Despite the negative aspects discussed in the paper, we should finish on a more promising note. Russia has made remarkable progress during the last decade. There is a constitution. There are elections and elected institutions, which function extremely badly, but no one has seriously urged their abandonment. One of the outstanding features of the century is the patience of the Russian people in the face of the terrible conditions in which they have been forced to live.

SELECTED REFERENCES Aganbegyan, Abel (1988), The Economic Challenge of Perestroika, Indiana University Press, Bloomington Ind. Arthur, W.B. (1994), Increasing Returns and Path Dependence in the Economy, University of Michigan Press, Ann Arbor. Central Bank of Russian Federation (1998), Main Macroeconomic Indicators in 1998, Internet, homepage, http://www.cbr.ru/eng/dp/macroec%5F98.htm Central Bank of Russian Federation (1998), Main Macroeconomic Indicators in 199497, Internet, homepage, http://www.cbr.ru/eng/dp/macroec%5F94%2D97.htm. Corbin, Henry, (1969), Creative Imagination in the Sufism of Ibn ‘Arabi, Bollingen Series XCI, Princetown University Press, Princetown. Durlauf (1996) Statistical mechanics Approaches to Socioeconomic Behaviour, Working Paper, 96-08-069, for the SFI Economice Research Program, Santa Fe Institute. Credit Suisse First Boston (1995), A Guide to Russian Debt Markets, December. Euromoney (1997), The 1997 Guide to the Russian Financial Markets, March Euromoney (1998), "Back to the age of defaults", No 355, November, p.p. 60-63 Euromoney (1998), "A superpower falls apart", No 353, September, p.p. 56-64 Euromoney (1998), "Fedorov: Russia's taxman", No 353, September, p.p. 66-62 Gaddy, C.G. (1996), The Price of the Past: Russia's Struggle with the Legacy of a Militarized Economy, Washington DC, Brookings Gaddy, C.G. and Ickes, B.W. (1998), Russia's Virtual Economy, Foreign Affairs, Volume 77, No.5, September-October, p.p. 53-67 Gavrilenkov, E. and V. Koen (1995), "How large was the Output Collapse in Russia? Alternative Estimates and Welfare Implications", Staff Studies for the World Economic Outlook, International Monetary Fund, Washington DC, p.p. 106119 Golov, R.S. (1998), "Problema neplatezhey v sovremennoy rossiyskoy ekonomike i organizatciia sistemy regionalnych vekselnych raschetov mezhdu mestnym budgetom i predpriiatiiami regiona kak odin iz sposobov eye preodoleniia", Innovatcii Volume 14-15, No. 4-5, October, p.p. 70-78 Golov, R.S. and Matthews, R., (1999) The Russian crisis: Causes, Consequences, and Implications for the Future, Occasional Paper, Kingston University.

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Gowan, Peter (1995) Analysing Shock Therapy, New Left Review, 213, London. Holmstrom, B. and Tirole, J. (1989), The Theory of the Firm, in R. Schmalensee and R. D. Willig (Eds.), Handbook of Industrial Organisation, Vol. 1, Handbooks of Economics, No 10, Amsterdam, North-Holland, p. 61-133. Keynes, J.M. (1936), The General Theory of Money Interest and Prices, Macmillan, London Kauffman, S. (1993), The Origins of Order: Self-Organization and Selection in Evolution, Oxford University Press, New York. Krugman, P. (1998) 'What happened to Asia?,' mimeo, MIT, January. Krugman (1998), 'Don't Panic -- YET', Krugman Home Page, Internet. Kuboniwa, M. and E. Gavrilenkov (1997), Development of Capitalism in Russia: The Second Challenge, Maruzen Co., Tokyo. Landau, L. D. and Lifshitz, M. E. (1975), Statistical Physics, Pergamon. Matthews Robin (1999a) Strategy and Cooperative Games, in Sami Daniel, Philip Atestis and John Grahl, Ed. Regulation Strategies and Economic Policies: Essays in Honour of Bernard Corry and Maurice Peston, Vol.3.Edward Elgar, London. Matthews, Robin (1999b), Complexity and Strategic Planning: A Statistical Mechanics Approach, Proceedings of the International Federation of Operational Research Societies Conference, (IFORS 1999), Beijing. Matthews, Robin, (1998) The Myth of Global Competition and the Nature of Work, Journal of Organizational Change Management, Vol.11. No.5. Matthews, Robin, and A.Yeghiazarian, Russian Management Style: A Game Theory Approach to Evaluating Decision-Making, Journal of east European Management Studies, Vol. 3. No 1. Merzard, M., Parisi, G., and Virasoro, M. A. (1987), Spin Glass Theory and Beyond, World Scientific. Myerson, R. B. (1991), Game Theory: Analysis of Conflict, Harvard University Press, London. Nozick, Robert, (1995), The Nature of Rationality, Princetown University Press, Chichester, UK. Radner, Roy, (1984) Information, incentives and economic mechanisms: essays in honour of Leonid Hurwicz, Blackwell Ruelle, D. (1987), Theory and Experiment in the Ergodic Study of Chaos and Strange Attractors, 8th Intl. Congress on Mathematical Physics, Eds. M. Mebkhout and R. Sϑnϑor, World Scientific, p. 273-282. Ruelle, D. (1988), Can Non-linear Dynamics Help Economists? in The Economy as an Evolving Complex System—The Proceedings of the Evolutionary Paths of the Global Economy Workshop held September 1987 in Santa Fe New Mexico, Eds. P. W. Anderson, K. J. Arrow, and D. Pines, Addison-Wesley Publishing Company, p. 195-204. Sachs, Jeffrey (1994), Understanding Shock Therapy, Social Market Foundation, London. Sachs, Jeffrey (1990), What is to be Done? Economist,13. January. Segodnia (1996), "Zadolzhennost biudzhetu 94 krupneishikh dolgnikov prevysla 34 trillionov rublei", 20 December Shelley, Louise (1997), "The Price Tag of Russia's Organized Crime", Transition, Vol. 8, No 1, p.p. 7-8 Shlykov, Vitaly (1997), The crisis in the Russian economy, Internet, homepage, http://www.milnet.com/milnet/rusmil97/crisisp1.htm

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Simon, H.A. (1980), Models of Man; Social and Rational, New York Wiley. Skvortsov, V. (1997), "Most nad biudzhetom", Kommersant, No 16, p.13 State Tax Service (1997), "Materialy k zasedaniiu prezidiuma pravitelstva Rossiiskoi Federatsii po voprosu "O merrakh po usileniiu gosudarstvennogo kontrolia za nalogovoi distsiplinoi krupnykh kompanii I predpriiatii - neplatelshikov" (materials prepared for the federal government) Teece D. J. and G. Pisano (1994), The Dynamic Capabilities of Firms: An Introduction, Industrial and Corporate Change, Vol. 3, No.3. Tikhomirov, V. (1997), "Capital Flight from Post-Soviet Russia", Europe-Asia Studies, Vol. 49, No 4, p.p. 591-615

NOTES i

I am grateful to Sue Balmer, Zakhar Bolshakov, Maureen Beard, and Roman Golov for comments on earlier drafts. ii See for example Castells (1998). In my view this is a classic work. iii There are many good texts in the area. On complexity see Coveney and Highfield (1995), Landau and Lishitz (1975), Kauffman (1993), Mezard, Parisi and Visasoro (1987). On games see, Holmstrom and Tirole (1985) and Myerson (1991) iv The picture is ambiguous and complex since regionalism, localization are part of the process and in some ways the world economy is less integrated than it was in the late nineteenth century. See for example Hirst and Thomson (1996) and Matthews (1998). v Holland's notion of a transition function, (Holland,1998) is similar. vi There are many references here. For a good account of the early periods see Aganbegyan (1998). For an idealized market approach contemporary analysis see Sachs (1990, 1994). Peter Gowans (1995) account of Shock Therapy is penetrating. For a discussion of the recent situation see the selected bibliography. The virtual economy is analysed by Gaddy (1996) and Gaddy and Ickes (1998). vii For this section see Durlauf (1996) and Matthews (1999a and b). viii Simon (1980). ix For an exhaustive analysis of networks see Castells (1998). x Teece and Pisano (1994). xi The key reference from Western sources is of course Heidegger. The paper draws mainly on Eastern philosophy here. See for example Corbin (1969). xii : "For my own part I believe there is social and psychological justification for significant inequalities of wealth, but not for such large disparities as exist today. There are valuable human activities which require the motive of money making............But it is not necessary for the stimulation of these activities and stimulation of these proclivities that the game should be played for such high stakes as at present." (Keynes,1936). xiii See Corbin above. The unveiling image is part of the Sufi hermeneutic tradition. xiv Figure 1 indicates that there are activities within activities within activities and so on. One implication of the fractal nature of activities is that dynamic capabilities, or core competencies, that is sources of competitive advantage that it is difficult for rivals to copy, (if they exist) essentially lie in a network of activities that span different levels of organization (firms, businesses, teams, and so on) as well as linking different parts of the same (level of) organization. Since, in times of rapid change and shortening product cycles, they are also likely to involve the capacity to adapt and learn, that is grasp new potentialities, they also likely to embrace different levels of being. xv

Already the sales of Wal-Mart ($119bn.) exceed the GNP of Greece; Volkswagen AG sales ($65bn.) exceed the GNP of Egypt, Mitsubishi Corporation ($129bn.), South Africa; Sony Corporation ($55bn.), the Czech Republic and General Electric ($91bn.), Israel. xvi Denoting interdependent payoffs between activities k and j as bij, and cooperative variables as Sk and Sj we have the relationship bkj ∼ SkSj 0 ≤ S ≤ 1. See Matthews (1999). xvii

See Nozik (1995).

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xviii

The situation is like forming a team of Blue, Orange, Pink, Green and Purple, for example, and getting them to cooperate, when Blue and Orange dislike one another, but Blue likes Pink, and Pink hates Purple but Green likes them all, and Purple won't say. It becomes much more complex when there are many people. xix See Arthur (1994), for analysis of such path dependent processes. xx See Radner's collection in Honour of Leonid Hurwicz (1984). xxi The phrase is Brian Arthur’s. Much of this section draws on his work: see Arthur (1994). xxii Euromoney 353, 355 (1998), Krugman (1998), Piranfar (1999). xxiii See note xxii. xxiv Matthews and Yeghiazarian (1998) xxv To achieve this a convex hull of extreme points is formed. xxvi It is NP complete. xxvii So is P(2), because it is a proper subset of P(1). For a discussion of attractors see Ruelle (1987, 1988) xxviii A forthcoming paper by Golov and Matthews considers this in detail.

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