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Thinking Small and Long: Service-Dominant Logic & Agent Based Modeling . Robert F. Lusch Lisle & Roslyn Payne Professor of Marketing University of Arizona University of Hawaii March 10, 2006. Small and Long Thinking . S-D Logic & ABM as a Paradigm Shift: From Constructs to Actors.

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Thinking Small and Long: Service-Dominant Logic & Agent Based Modeling


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    1. Thinking Small and Long:Service-Dominant Logic & Agent Based Modeling Robert F. Lusch Lisle & Roslyn Payne Professor of Marketing University of Arizona University of Hawaii March 10, 2006

    2. Small and Long Thinking

    3. S-D Logic & ABM as a Paradigm Shift:From Constructs to Actors • Virtually all social science theory models relations between constructs. • S-D logic views marketing as interactions between entities and ABM provides the method to model and research these interactions. • What emerges from interactions? • Macro structures • Relations between variables • Rules (institutions and norms) • Co-creation

    4. Building Markets from Ground Up Object Oriented Programming

    5. Object Oriented Programming • OOP Integrates Data and Functions. • Every digital organism is an object with its own information and functions it uses to operate. • Every digital organism has receptors, memory, decision system, and effectors.

    6. Creation of Digital Life Object Oriented Software Program Environment Memory Capability Sensory Capability Effector Capability Learning & Decision Capability Environment

    7. Genetic Algorithms & Digital Learning

    8. Decision-Making: From Substantive Rationality to Procedural Rationality • Simon (1978) argues the concept of rationality is “economics” main export to other social sciences. • In complex environments actors evolve and their actions and anticipations are unknown from each other; the relevant rationality is procedural rationality. • These environments are the “permanent and ineradicable scandal of economic theory” (Simon 1976). • Mind is the scarce resource; how the actor finds efficient and effective search algorithms is the key.

    9. Procedural Rationality: How do Individuals Reason & Learn? • Inductive reasoning—ampliative method of reasoning (gap filling) • Extinguish rules or actions that are unsuccessful and adopt rules or actions that are successful—market hypotheses • Information processing and actions not fine-grained but are fuzzy • Memory lingers; little is completely forgotten

    10. Lack of crisp, well-defined boundaries Membership in two or more sets Imprecise linguistic concepts Everything a matter of degree Speed of perception and information processing Weekend Days Fuzzy Logic Saturday Sunday Friday

    11. A Pair of Interesting Observations • What used to work no longer works? • Competitive dynamics • Competition is a disequilibrating process • If it works don’t fool with it. • Learning via exploitation • Learning via exploration • The ambidextrous organization

    12. Real Competitive Markets • Competition is an evolutionary & disequilibrating process (Schumpeter 1934; Alchian 1950; Nelson & Winter 1982) • Competition occurs in uncertain world and competition is a knowledge discovery process (Hayek 1935) • Demand and supply are heterogeneous (Chamberlain 1933; Alderson 1957, 1965) • Competition involves a struggle for advantage (Clark 1954; Alderson 1957, 1965) • History counts (North 1981; Chander 1990) • Entities constantly strive to do better (Bain 1954, 1956) • Resources are tangible and intangible and imperfectly mobile (Penrose 1959; Lippman & Rumelt 1982). • Knowledge is the fundamental source of competitive advantage (Vargo & Lusch 2004).

    13. Competitive Dynamics:Simple Rules • Sellers must independently decide on price, advertising, product attributes, inventory level. • Seller has four fuzzy states (low, moderately low, moderately high, high) for each of four decisions. 44= 256 rules • These 256 rules form a “market hypothesis” • Ten rule bases characterize 10 market hypotheses each seller uses. • Utilization of which market hypothesis to use is based on their fitness.

    14. Simple Setting: Complex Market

    15. How Fuzzy Inputs Interact to Affect Price Decision

    16. Evolution of Profit Payoff from Price: Seller-1

    17. Evolution of Profit Impact from Price Across Sellers

    18. Evolution of Cross Profit Impact from Price: Sellers 1 &2

    19. The Ambidextrous Organization & Evolutionary Biology • When the environment changes slowly then mechanisms of exploitation that work on variation, selection and retention work well.We learn by communicating and do this primarily by crossover. • When there is dramatic shift in the environment or a punctuated equilibria then relying purely on exploitation will not allow the organism to survive. It must explore to innovate or face extinction.

    20. The Ambidextrous Organization: Modeling Exploitation with Crossover Moderate Crossover (moderate exploitation) is represented by 50% probability of crossover every 30 periods. High Crossover (high exploitation) is represented by 100% probability of crossover every 30 periods. In this situation the seller takes advantage of every opportunity to investigate the space for a good solution.

    21. The Ambidextrous Organization: Modeling Exploration with Mutation High Mutation (high exploration) is represented by 50% probability of mutation every 30 periods. Moderate Mutation (moderate exploration) is represented by 25% probability of mutation every 30 periods. Low Mutation (low exploration) is represented by 5% probability of mutation every 30 periods.

    22. Simple Setting: Complex Market

    23. Organizational Learning Strategies

    24. Market-A: Stable World • Buyer preferences are fixed or unchanging. • In this situation we would expect the organization that focuses heavily on exploitation as a learning mechanism and seldom uses exploration to learn to perform best (seller four). On the other hand an organization with high exploration would do poorly (seller one).

    25. Stable World

    26. Market B: Turbulent World • Buyer preferences are randomly changed every 1500 periods (50*crossover frequency). • In this situation we would expect ambidextrous organizations to do best. The organizations that both, to a good degree, exploit and explore. This would be sellers 2 or 3. Seller four who hardly ever explores should perform the poorest.

    27. Turbulent World

    28. Profit Payoffs

    29. Moderating Effect:Market Environment(average profit)

    30. Concluding Observations