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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 Robert F. Lusch Lisle & Roslyn Payne Professor of Marketing University of Arizona University of Hawaii March 10, 2006
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
Building Markets from Ground Up Object Oriented Programming
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.
Creation of Digital Life Object Oriented Software Program Environment Memory Capability Sensory Capability Effector Capability Learning & Decision Capability Environment
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.
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
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
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
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).
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.
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.
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.
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.
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).
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.
