David M. Smith’s locational theory represents a significant departure from traditional neoclassical location models by introducing behavioral realism, spatial margins, and satisficing behavior into industrial location analysis. Developed during the 1960s and 1970s, Smith’s behavioral approach challenged the rational optimization assumptions of earlier theories by recognizing that real-world decision-makers operate under incomplete information, bounded rationality, and multiple objectives that prevent them from achieving truly optimal locations.
Smith’s theoretical framework bridges the gap between abstract economic models and empirical observations of actual location behavior by incorporating psychological factors, organizational constraints, and information limitations that influence industrial location decisions. His spatial margins to profitability concept and behavioral matrix provide tools for understanding why firms may choose suboptimal locations while still achieving satisfactory performance and business survival.
The significance of Smith’s contribution lies in its realistic portrayal of location decision-making as a complex process involving multiple actors, conflicting objectives, uncertainty, and satisficing strategies rather than the mechanical optimization assumed by traditional location theory. This behavioral perspective has influenced contemporary approaches to economic geography, regional development, and business location analysis.
Table of Contents
Theoretical Context and Development
Critique of Classical Location Theory
Smith’s theoretical development emerged from fundamental criticisms of classical location models that assumed perfect information, rational optimization, and single-objective decision-making. Weber’s least-cost theory, Lösch’s market area analysis, and Hotelling’s spatial competition model all relied on unrealistic assumptions about decision-maker behavior and market conditions that rarely exist in real-world situations.
Perfect information assumption in classical models ignores the reality that location decision-makers have limited knowledge about cost structures, market conditions, competitor behavior, and future economic trends. Information gathering itself involves costs and time constraints that make complete knowledge practically impossible and economically inefficient.
Rational optimization assumption presupposes that decision-makers have clear objectives, consistent preferences, and unlimited computational abilities to identify optimal solutions. However, real organizations often have multiple stakeholders with conflicting goals, bounded rationality that limits information processing, and satisficing behaviors that seek acceptable solutions rather than optimal outcomes.
Single-objective focus on profit maximization or cost minimization oversimplifies complex organizational realities where firms may prioritize market share, risk minimization, growth opportunities, social responsibility, or managerial preferences alongside or instead of pure economic optimization. Multiple objectives create trade-offs that classical models cannot adequately address.
Behavioral Economics Influence
Herbert Simon’s behavioral economics and satisficing theory provided the conceptual foundation for Smith’s behavioral approach to location analysis. Simon’s insights about bounded rationality, information costs, and satisficing behavior directly challenged neoclassical assumptions about rational economic actors and optimization behavior.
Bounded rationality concept recognizes that human decision-makers have cognitive limitations that prevent them from processing all available information and considering all possible alternatives. Decision-makers use heuristics, rules of thumb, and simplified models to make manageable decisions within their cognitive constraints and time limitations.
Satisficing behavior describes how decision-makers seek solutions that meet minimum criteria for acceptability rather than optimizing across all possible alternatives. Satisficing strategies reduce decision-making costs and complexity while achieving satisfactory outcomes that enable organizational survival and goal attainment.
Organizational theory contributions from James March, Richard Cyert, and other behavioral economists highlighted how complex organizations make decisions through political processes, coalition building, and sequential attention to different goals rather than unified optimization of single objectives.
Geographic and Economic Context
Quantitative revolution in geography during the 1960s emphasized spatial analysis, mathematical modeling, and scientific methods that initially embraced neoclassical economic assumptions. However, growing dissatisfaction with purely quantitative approaches and recognition of their empirical limitations created openness to alternative theoretical frameworks.
Industrial geography research revealed significant gaps between theoretical predictions and observed location patterns that could not be explained by traditional models. Case studies of actual location decisions showed complex processes involving multiple factors, subjective judgments, and organizational politics that formal models could not capture.
Regional development policy experiences demonstrated that location incentives and planning strategies based on traditional theory often failed to achieve expected results, suggesting that real location behavior differed significantly from theoretical assumptions. Policy failures created demand for more realistic theories that could better inform practical decision-making.
Core Concepts of Smith’s Theory
Spatial Margins to Profitability
Spatial margins to profitability represents Smith’s central theoretical innovation, defining the geographic boundaries within which a firm can operate profitably at any given location. This concept moves beyond point optimization to recognize that multiple locations may offer acceptable profitability levels even if they are not theoretically optimal.
Profitability surface in Smith’s model shows how profit levels vary across geographic space based on transportation costs, labor costs, market access, raw material availability, and other location-specific factors. The highest point on this surface represents the optimal location, while the margins define the boundaries of profitable operation.
Spatial margins are determined by the minimum profit level required for business survival and continued operation. Firms operating within these margins achieve satisfactory profitability even if they do not maximize profits, while locations outside the margins result in business failure or forced relocation.
Margin variability reflects differences in firm characteristics, technology, management efficiency, and competitive advantages that enable some companies to operate profitably in locations where others would fail. Efficient firms have wider spatial margins than inefficient competitors, providing greater locational flexibility.
Dynamic margins change over time as market conditions, technology, transportation costs, and competitive pressures evolve. Expanding margins increase locational options, while contracting margins force firms to relocate or improve efficiency to maintain profitability.
Behavioral Matrix and Decision-Making
Smith’s behavioral matrix provides a framework for analyzing location decisions based on decision-maker abilities and information quality rather than assumed optimization. This matrix distinguishes between different types of decision-making situations and expected outcomes based on behavioral characteristics.
Ability dimension in the behavioral matrix ranges from limited to comprehensive decision-making capabilities based on management skills, analytical resources, experience, and organizational sophistication. Highly capable decision-makers can process more information, consider more alternatives, and make better location choices than less capable counterparts.
Information dimension varies from poor to excellent information quality depending on data availability, research efforts, local knowledge, and environmental uncertainty. Better information enables more informed location decisions, while poor information leads to suboptimal choices and higher failure risks.
Matrix combinations create four types of decision-making situations: optimal decisions (high ability, good information), suboptimal decisions (high ability, poor information), lucky accidents (low ability, good information), and poor decisions (low ability, poor information). Real-world outcomes depend on these behavioral combinations rather than theoretical optimization.
Satisficing zones within the behavioral matrix identify ranges of acceptable decisions that may not be optimal but achieve satisfactory results given decision-maker constraints and information limitations. Firms operating within satisficing zones can survive and prosper without achieving theoretical optimality.
Learning and Adaptation
Organizational learning in Smith’s framework recognizes that firms improve their location decisions over time through experience, feedback, and adaptive behavior. Learning processes enable companies to expand their spatial margins, improve their decision-making abilities, and respond more effectively to changing conditions.
Trial and error learning occurs when firms experiment with different locations and learn from successes and failures. Multi-plant companies often use experimental strategies to test new markets and locations before making major commitments, reducing risks through incremental learning.
Imitation and following behavior represent common learning strategies where firms copy the location decisions of successful competitors rather than conducting independent analysis. Industrial clustering often results from imitative behavior where firms follow industry leaders to proven locations.
Information sharing within industry networks, professional associations, and regional clusters enables collective learning that improves individual firm decision-making. Shared knowledge about location factors, market conditions, and business practices reduces information costs and decision uncertainty.
Feedback mechanisms between location choices and business performance provide learning opportunities that influence future decisions. Successful locations reinforce decision-making approaches, while failures motivate strategy changes and improved analysis.
Applications and Empirical Evidence
Manufacturing Location Studies
Smith’s empirical research on manufacturing location decisions provided extensive evidence for behavioral approaches to location analysis. Case studies of various industries demonstrated significant deviations from theoretical predictions and highlighted the importance of behavioral factors in real-world location choices.
New England textile industry studies revealed how historical factors, family ties, local knowledge, and risk aversion influenced firm locations more than pure economic optimization. Established companies often remained in suboptimal locations due to sunk costs, local connections, and uncertainty about relocation benefits.
Footloose industries analysis showed that firms with limited location constraints often made location decisions based on managerial preferences, quality of life considerations, and personal factors rather than cost minimization. Electronics and software companies frequently prioritized amenities and lifestyle factors alongside economic considerations.
Branch plant locations demonstrated how large corporations use satisficing strategies to select acceptable locations from predetermined regions rather than conducting comprehensive global searches. Investment timing pressures and organizational constraints often limit location analysis to satisficing rather than optimizing approaches.
Small business location studies showed that entrepreneurs often choose locations based on personal familiarity, limited search areas, and immediate availability rather than systematic analysis of all possible alternatives. Information limitations and resource constraints make comprehensive location analysis impractical for many small firms.
Service Sector Applications
Service industry location analysis using Smith’s framework revealed different patterns of behavioral decision-making compared to manufacturing firms. Service businesses often prioritize customer access, market visibility, and convenience factors that create different spatial margins and decision-making processes.
Retail location decisions demonstrate satisficing behavior where store owners select acceptable sites from available options rather than optimizing across all possible locations. Lease availability, timing constraints, and capital limitations often determine location choices more than theoretical optimization.
Office location studies show how corporate headquarters and professional services balance economic factors with prestige, accessibility, and agglomeration benefits that create complex trade-offs resistant to simple optimization. Central business districts maintain attractiveness despite higher costs due to symbolic value and network effects.
Financial services location analysis reveals conservative decision-making approaches that prioritize risk minimization and regulatory compliance over profit maximization. Bank branch networks often exhibit satisficing patterns that maintain market presence and customer service rather than optimizing cost structures.
Healthcare facility location demonstrates how public service and social responsibility objectives influence location decisions alongside economic considerations. Hospital systems may maintain facilities in marginal locations to serve community needs despite limited profitability.
International Business Applications
Multinational corporation location decisions provide rich examples of behavioral approaches where complex organizations navigate multiple objectives, regulatory environments, and cultural contexts that prevent simple optimization. International business location analysis highlights information limitations and satisficing strategies.
Foreign direct investment studies show how multinational firms use incremental approaches and satisficing strategies when entering new markets rather than conducting comprehensive global optimization. Market entry often begins with acceptable locations that provide learning opportunities for subsequent expansion.
Global production networks demonstrate sequential decision-making processes where firms establish regional operations and gradually optimize their networks through experience and learning rather than designing optimal configurations initially. Path dependence and organizational inertia influence network evolution.
Joint venture locations reflect complex negotiations and compromises between partners with different objectives and constraints that rarely result in theoretically optimal solutions. Partnership dynamics and political considerations often override pure economic logic in location choices.
Export processing zones and special economic zones attract foreign investors through satisficing approaches that offer acceptable combinations of incentives, infrastructure, and market access rather than globally optimal locations. Policy packages create spatial margins that enable profitable operation across multiple sites.
Spatial Margins Analysis
Determining Profitability Boundaries
Spatial margins analysis requires identifying the geographic boundaries within which firms can operate profitably given their specific characteristics and market conditions. This analysis involves mapping cost variations, revenue potential, and profit levels across different locations to define feasible operating areas.
Cost surface mapping identifies how production costs, transportation expenses, labor costs, and other location-specific factors vary across geographic space. Isocost lines connect points of equal cost and help visualize how cost disadvantages increase with distance from optimal locations.
Revenue surface analysis examines how market access, demand levels, competition intensity, and pricing opportunities affect potential revenues at different locations. Market areas, catchment zones, and competitive territories influence revenue generation and spatial profit variations.
Profit surface construction combines cost and revenue surfaces to identify profit levels at each location and determine the spatial extent of profitable operation. Isoprofit lines connect points of equal profitability and define the margins beyond which operation becomes unprofitable.
Minimum profit thresholds determine the spatial margins based on survival requirements, opportunity costs, and investor expectations. Different firms may have different threshold levels based on their financial situation, risk tolerance, and strategic objectives, creating varying spatial margins for similar businesses.
Factors Affecting Margin Width
Technological efficiency significantly influences spatial margin width by affecting production costs and competitive advantages. More efficient firms can operate profitably in marginal locations where less efficient competitors would fail, expanding their locational options and strategic flexibility.
Product differentiation and brand strength enable firms to charge premium prices that offset location disadvantages and expand spatial margins. Unique products, strong brands, and customer loyalty create pricing power that reduces location sensitivity and increases viable location options.
Scale economies affect spatial margins by influencing minimum viable plant sizes and market areas. Large-scale operations may require extensive market areas that limit location options, while small-scale flexible production may enable operation in smaller markets with wider spatial margins.
Transportation infrastructure and logistics capabilities determine how distance affects costs and market access, directly influencing spatial margin width. Improved transportation expands spatial margins by reducing distance penalties, while poor infrastructure contracts margins and limits location choices.
Market structure and competition levels affect spatial margins through pricing pressures and market share considerations. Monopolistic or oligopolistic markets may provide wider margins due to limited competition, while highly competitive markets create narrow margins that restrict location flexibility.
Dynamic Margin Changes
Technological change continuously alters spatial margins by changing production processes, transportation costs, communication requirements, and competitive advantages. Innovation can expand or contract margins depending on whether new technologies favor concentration or dispersion of economic activities.
Market evolution through demand growth, consumer preference changes, new product development, and competitive entry affects spatial margins by altering revenue potential and profit opportunities across different locations. Growing markets may expand margins, while declining markets may contract them.
Infrastructure development including transportation improvements, communication networks, and utility expansions can dramatically alter spatial margins by changing relative location advantages and accessibility patterns. New infrastructure may create opportunities in previously marginal locations while reducing advantages of traditional centers.
Policy changes through taxation, regulations, incentives, and trade policies directly influence spatial margins by affecting location-specific costs and benefits. Government interventions can artificially expand margins in targeted areas while contracting them elsewhere through policy instruments.
External shocks such as energy crises, natural disasters, economic recessions, and geopolitical events can rapidly alter spatial margins by changing fundamental location factors and market conditions. Firms must adapt to these changes or risk falling outside viable operating areas.
Behavioral Decision-Making Models
Information and Search Behavior
Information acquisition in Smith’s model involves costs, time constraints, and diminishing returns that limit the extent of location search and analysis. Rational decision-makers balance information costs against potential benefits of improved decisions, often stopping search processes before achieving complete information.
Search strategies vary from comprehensive surveys of all possible locations to limited searches within predetermined areas or among known alternatives. Most firms use bounded search that focuses on familiar regions, recommended sites, or areas that meet basic criteria rather than examining all possibilities.
Information sources include formal studies, professional consultants, government agencies, industry associations, and informal networks that provide different types and qualities of location information. Information quality and relevance vary significantly across sources, affecting decision-making effectiveness.
Uncertainty about future conditions, competitor behavior, market trends, and policy changes complicates location decisions and encourages conservative or flexible approaches that may not optimize current conditions but provide adaptability for future changes.
Learning from others through industry networks, professional contacts, and competitor observation provides cost-effective information gathering that influences location choices. Imitation and following behavior reduce information costs but may lead to suboptimal clustering or missed opportunities.
Risk and Uncertainty Management
Risk perception influences location decisions through decision-maker risk tolerance, past experiences, and organizational culture that may lead to conservative choices even when aggressive strategies might yield higher returns. Risk aversion tends to favor familiar locations and proven strategies over innovative approaches.
Uncertainty reduction strategies include incremental expansion, joint ventures, licensing agreements, and pilot projects that limit exposure while providing learning opportunities. Sequential decision-making allows firms to gather information and adjust strategies based on early results.
Portfolio approaches to location decisions diversify risks across multiple sites, markets, and regions rather than concentrating operations in single locations that might optimize current conditions but create vulnerability to local disruptions or market changes.
Flexibility preservation influences location choices toward sites that maintain options for future expansion, contraction, or strategic changes even if immediate costs are higher than more specialized but less flexible alternatives.
Insurance and hedging strategies may influence location decisions by affecting relative costs and risks of different sites. Political risk insurance, currency hedging, and supply chain insurance can alter location calculations and spatial margins.
Organizational Decision Processes
Multiple stakeholders in location decisions include owners, managers, employees, shareholders, and community representatives who may have conflicting objectives and different priorities that prevent simple optimization of single criteria. Decision processes must balance these diverse interests.
Coalition building within organizations involves negotiations and compromises among different groups that may result in location choices that satisfy key stakeholders rather than optimizing economic outcomes. Political processes within firms influence final decisions.
Sequential attention to different objectives means that organizations may focus on different criteria at different times rather than simultaneously optimizing all factors. Location decisions may prioritize immediate needs while deferring consideration of longer-term factors.
Standard operating procedures and organizational routines simplify decision-making by applying established criteria and procedures rather than conducting fresh analysis for each decision. Routinized decisions reduce costs and complexity but may miss new opportunities or changing conditions.
Time constraints and decision deadlines force organizations to make choices with incomplete analysis and limited alternative evaluation. Satisficing under time pressure often produces acceptable but suboptimal location decisions.
Critiques and Extensions
Theoretical Limitations
Measurement difficulties in Smith’s framework include problems in defining and quantifying spatial margins, profitability levels, and behavioral variables that make empirical testing and practical application challenging. Profit data is often proprietary and spatial variations may be difficult to observe directly.
Static analysis in Smith’s original formulation focuses on decision-making at particular points in time rather than fully addressing dynamic processes of learning, adaptation, and strategy evolution that characterize real-world business behavior over extended periods.
Limited consideration of institutional factors, power relationships, and structural constraints that influence location decisions beyond individual firm behavior. Government policies, labor relations, financing availability, and social factors may override firm-level behavioral considerations.
Cultural and social factors receive insufficient attention in Smith’s framework, despite evidence that cultural differences, social networks, and community relationships significantly influence location decisions, particularly for small businesses and family enterprises.
Scale dependency means that behavioral factors may vary in importance across different firm sizes, industries, and organizational types. Large corporations may have different behavioral patterns than small businesses, requiring differentiated theoretical approaches.
Empirical Challenges
Data availability for testing behavioral theories often proves limited because decision-making processes, information quality, and managerial capabilities are difficult to observe and measure objectively. Survey methods may suffer from response bias and retrospective distortion.
Case study limitations include problems of generalization from specific situations to broader patterns, selection bias toward interesting or successful cases, and difficulty in isolating behavioral factors from other influences on location decisions.
Longitudinal studies required for understanding learning and adaptation processes are expensive and time-consuming, while firm populations may change through mergers, closures, and new entries that complicate long-term analysis.
Cross-cultural validation of behavioral patterns remains limited, with most studies focused on Western industrialized countries. Different cultural contexts may produce different behavioral patterns that limit theoretical generalization.
Technology impacts on information availability, communication costs, and decision-making tools may alter behavioral patterns in ways that historical studies cannot predict. Digital technologies may reduce some information limitations while creating new forms of complexity.
Contemporary Relevance
Globalization has expanded location choices and information sources while creating new forms of complexity and uncertainty that may strengthen satisficing approaches rather than enabling optimization. Global supply chains and international markets increase information requirements beyond most firms’ processing capabilities.
Digital technologies provide new tools for location analysis and decision support but may not eliminate fundamental behavioral constraints related to bounded rationality, risk perception, and organizational politics. Information overload may actually worsen decision-making in some situations.
Environmental concerns and sustainability requirements add new dimensions to location decisions that complicate traditional economic calculations and may strengthen satisficing approaches that balance multiple objectives rather than optimizing single criteria.
Service economy growth and knowledge-based industries may exhibit different behavioral patterns than the manufacturing firms that Smith primarily studied. Creative industries, professional services, and technology firms may prioritize different factors and use different decision processes.
Policy implications of behavioral approaches suggest that location incentives and development strategies should consider actual decision-making processes rather than assume rational optimization. Information provision, risk reduction, and simplification may be more effective than complex incentive schemes.
Contemporary Applications
Regional Development Policy
Economic development agencies apply Smith’s insights by recognizing that businesses use satisficing approaches rather than comprehensive optimization when making location decisions. Development strategies focus on creating acceptable packages of incentives and amenities rather than trying to optimize single factors.
Business incubators and enterprise zones create spatial margins for new businesses by reducing operating costs and providing support services that enable survival in locations that might otherwise be marginal. These programs recognize that small businesses often lack resources for comprehensive location analysis.
Information services provided by development agencies help reduce search costs and improve decision-making quality for location decisions. Site selection assistance, market research, and regulatory guidance address information limitations that behavioral theory identifies as key constraints.
Infrastructure development strategies aim to expand spatial margins for business location by improving transportation, communications, and utilities that reduce location-specific disadvantages. Industrial parks and business districts provide shared infrastructure that widens viable location options.
Cluster development policies leverage agglomeration effects and learning processes to create environments where firms can achieve satisfactory performance without individual optimization. Industry clusters provide collective benefits that expand spatial margins for participant firms.
Business Location Services
Location consulting industry applies behavioral insights by recognizing client limitations in information processing and decision-making capacity. Consultants provide simplified analyses, decision frameworks, and recommendations that enable satisficing decisions within client constraints.
Site selection methodologies incorporate behavioral factors by considering management preferences, organizational capabilities, and risk tolerance alongside economic factors. Multi-criteria analysis and weighted scoring methods reflect multiple objectives and trade-offs in real decisions.
Corporate real estate management uses portfolio approaches that balance optimization with flexibility and risk management. Companies maintain multiple facilities that may not individually optimize costs but collectively provide strategic advantages and operational resilience.
International expansion services address information limitations and uncertainty that characterize foreign market entry. Market research, cultural training, and risk assessment help firms make satisficing decisions in complex international environments.
Technology platforms for location analysis recognize bounded rationality by providing simplified interfaces, automated analysis, and decision support tools that enhance decision-making capabilities within realistic constraints on time and expertise.
Supply Chain Management
Supplier selection processes often exhibit satisficing behavior where firms choose acceptable suppliers from limited searches rather than optimizing across all possible options. Vendor qualification systems define minimum standards that create spatial margins for supplier location.
Distribution network design balances multiple objectives including cost, service levels, flexibility, and risk management that prevent simple optimization. Companies often use satisficing approaches that achieve acceptable performance across multiple criteria.
Just-in-time production systems create spatial constraints that may override cost optimization in supplier location decisions. Proximity requirements define spatial margins within which suppliers must locate to participate in supply networks.
Risk management in supply chains encourages geographic diversification and redundancy that may sacrifice cost efficiency for operational resilience. Portfolio approaches to supplier location reflect satisficing strategies that balance multiple objectives.
Global sourcing decisions involve complex trade-offs between costs, quality, delivery, flexibility, and risks that make optimization difficult. Companies often use satisficing approaches that meet minimum requirements across multiple criteria.