Switching Cost (Information Search Burden) (SCISB)

1. Abstract

The Switching Cost (Information Search Burden) (SCISB) scale—originally operationalized as the Evaluation Costs subscale within the multidimensional consumer switching cost typology developed by Burnham, Frels, and Mahajan (2003)—is a specialized psychometric instrument designed to assess consumers’ subjective perceptions of the cognitive, temporal, and effortful investments required to gather, process, compare, and appraise alternative service providers. Rooted in transaction cost economics, economics of information, and bounded rationality theories, the SCISB isolates the pre-decisional informational friction that deters consumers from defecting from an incumbent provider, even in the presence of perceived market alternatives. Comprising four standardized items measured on a five-point Likert-type response scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree), the instrument specifically captures time constraints, the mental exertion needed to achieve evaluative comfort, the perceived difficulty of cross-provider comparative analysis, and the overarching friction of evaluating alternative offerings in complex service domains.

Psychometrically, the SCISB has demonstrated exceptional structural integrity, internal consistency reliability, and nomological validity across diverse service industries, including telecommunications, retail banking, cloud computing, health maintenance organizations (HMOs), and professional business-to-business (B2B) services. In the seminal validation study by Burnham et al. (2003), the scale exhibited high internal reliability with a Cronbach’s alpha coefficient exceeding .80, strong composite reliability (> .82), and an average variance extracted (AVE) surpassing the recommended .50 threshold, establishing robust convergent validity. Confirmatory factor analyses (CFA) across independent customer samples have repeatedly verified its unidimensional structure within the broader second-order procedural switching cost construct, demonstrating distinct discriminant validity against related facets such as learning costs, setup costs, economic risk costs, and post-switching relational investments. Consequently, the SCISB serves as an indispensable tool for consumer psychologists, service management scholars, and market strategists examining customer retention, churn mitigation, competitive market lock-in, and consumer decision inertia.

2. Keywords

Switching costs, information search burden, evaluation costs, procedural switching costs, consumer retention, customer churn, transaction cost economics, bounded rationality, consumer decision-making, cognitive effort, service marketing, psychometrics.

3. Authors

The theoretical typology and corresponding measurement operationalization of the Information Search Burden (Evaluation Costs) scale were established by:

• Thomas A. Burnham — Associate Professor of Marketing, Department of Marketing, College of Business, University of Nevada, Reno, Reno, Nevada, United States. Burnham’s scholarship focuses on consumer decision-making, consumer lock-in, marketing analytics, and relational exchange theory.
• Judy K. Frels — Clinical Professor of Marketing and Associate Dean of Executive Programs, Robert H. Smith School of Business, University of Maryland, College Park, Maryland, United States. Frels specializes in strategic marketing, customer relationship management, and technology adoption.
• Vijay Mahajan — John P. Harbin Centennial Chair in Business and Professor of Marketing, McCombs School of Business, The University of Texas at Austin, Austin, Texas, United States. Mahajan is a globally renowned scholar in product diffusion, market entry strategies, and quantitative marketing modeling.

Correspondence regarding the foundational instrument can be traced to the seminal publication: Journal of the Academy of Marketing Science, Volume 31, Issue 2, pp. 109–126 (2003).

4. Purpose

In modern service economies characterized by product parity, rapid technological innovation, and information abundance, service organizations dedicate substantial resources toward acquiring competitors’ customers while preventing the attrition of their existing client base. Traditional economic paradigms posited that in competitive markets, consumers effortlessly migrate between providers whenever an alternative delivers superior marginal utility or a lower price point. However, empirical consumer behavior persistently demonstrates marked levels of customer retention and inertia, even under conditions of declining satisfaction or uncompetitive pricing. To explain this behavioral phenomenon, consumer psychologists and marketing researchers have operationalized the concept of switching barriers, foremost among which are switching costs.

The primary purpose of the Switching Cost (Information Search Burden) (SCISB) scale is to measure and quantify the subjective psychological friction associated with identifying, gathering, screening, and evaluating prospective substitute providers. Unlike objective monetary switching penalties (such as contract cancellation fees) or social losses (such as the severance of interpersonal ties with service personnel), evaluation costs constitute an upfront, intangible psychological hurdle that consumers must overcome before any actual defection can take place. The SCISB captures the mental and temporal taxation that consumers anticipate or experience when contemplating a departure from their current status quo.

Theoretical Rationale and Scope

The instrument is anchored in the premise that information search is neither costless nor cognitively friction-free. In markets where service offerings are complex, multi-attribute, non-standardized, or opaque (e.g., mobile telecommunications rate plans, mortgage financing, enterprise software solutions, investment management), comparing alternatives imposes a heavy cognitive load. Consumers must:

• Identify which alternative vendors exist in the marketplace and filter out irrelevant or fraudulent options;
• Decode and normalize heterogeneous pricing structures, fee schedules, hidden costs, and service-level agreements (SLAs);
• Extrapolate whether the quality and reliability of an unfamiliar competitor will match or exceed their current baseline experience; and
• Synthesize disparate performance data under severe time constraints and bounded information-processing capacity.

The SCISB measures the consumer’s perception of this cumulative burden. When perceived information search costs are high, consumers experience evaluative paralysis and status quo bias, determining that the expected utility of locating a superior provider is outweighed by the immediate psychological, temporal, and energetic costs of conducting an exhaustive market comparison.

Research Applications

In academic research, the SCISB is widely utilized within structural equation modeling (SEM) frameworks to assess how search burdens mediate or moderate the relationships among customer satisfaction, perceived service quality, alternative attractiveness, and customer loyalty or churn intentions. It allows empirical researchers to decouple procedural cognitive barriers from contractual or social barriers, thereby isolating the unique variance in retention explained by information processing strain. In behavioral economics, the scale is deployed to measure the subjective parameters of consumer search models and to test hypotheses surrounding market friction, bounded rationality, and choice overload.

Clinical and Applied Strategic Applications

While primarily developed for organizational and consumer research, the conceptual principles of the SCISB have meaningful applications in applied settings such as healthcare management, consumer advocacy, and regulatory policy design:

• Healthcare and Insurance Decision-Making: In complex healthcare environments, such as selecting Medicare advantage programs, private health maintenance organizations (HMOs), or chronic care providers, patients frequently remain enrolled in suboptimal plans due to extreme information search fatigue and evaluative distress. Assessing the SCISB helps healthcare administrators and patient advocates identify when plan complexity creates unhealthy inertia, guiding interventions to simplify plan comparisons.
• Regulatory and Antitrust Policy: Consumer protection agencies and market competition watchdogs utilize information search burden assessments to determine whether predatory pricing structures, deliberate “confusopoly” strategies (deliberate obscuring of plan details), or excessive disclosure documents stifle natural market competition by artificially inflating consumer search costs.
• Service Design and Churn Prevention: For service organizations, the scale functions diagnostically. Incumbent firms use it to determine the strength of their natural cognitive defenses, while challenger firms use it to identify barriers they must dismantle through comparison tools, transparent onboarding, and automated migration services to entice competitors’ customers.

5. Psychological Construct

The psychological construct measured by the SCISB is situated at the intersection of cognitive psychology, microeconomics, and consumer decision theory. Burnham et al. (2003) established an overarching tripartite typology of switching costs:

1. Procedural Switching Costs: Involving the expenditure of time and psychological/mental effort (subdivided into economic risk costs, evaluation costs/information search burden, learning costs, and setup costs).
2. Financial Switching Costs: Involving the loss of financially quantifiable resources (subdivided into benefit loss costs and sunk cost perceptions).
3. Relational Switching Costs: Involving psychological or emotional discomfort caused by breaking interpersonal or organizational bonds (subdivided into brand relationship loss and personal relationship loss).

The SCISB operationalizes the second dimension of procedural switching costs: Evaluation Costs, commonly conceptualized in subsequent literature as the Information Search Burden. This construct encompasses four distinct, highly interrelated psychological facets:

1. Temporal Taxation (Time Constraints in Search)

Temporal taxation reflects the consumer’s subjective perception that gathering comprehensive market intelligence requires an unacceptably large commitment of time. Time is a finite, scarce personal resource; hence, evaluating competing alternatives represents an explicit opportunity cost. The consumer recognizes that hours spent scouring competitor websites, visiting physical branches, reading consumer reviews, analyzing terms of service, and consulting peers cannot be allocated toward leisure, professional responsibilities, or familial commitments. In fast-paced contemporary environments, the mere prospect of having to devote multiple hours or days to vendor comparisons generates anticipatory avoidance behavior.

2. Cognitive Exertion and Evaluative Comfort

This facet captures the psychological effort required to reach a threshold of psychological safety and confidence—termed “evaluative comfort”—prior to committing to a switch. Modern decision theory recognizes that consumers do not seek merely to choose, but to make defensible, regret-minimizing choices. Achieving sufficient confidence to justify abandoning an incumbent provider demands substantial mental processing: parsing ambiguous advertising claims, deciphering technical specifications, and weighing non-commensurate product features. When consumers perceive that reaching an informed, confident evaluation demands deep cognitive exertion, they experience mental fatigue, triggering cognitive conservation mechanisms that preserve the status quo.

3. Cross-Provider Incommensurability (Difficulty of Comparison)

A central obstacle in modern service landscapes is the deliberate or structural incommensurability of service offerings. Providers frequently employ differentiated pricing structures (e.g., tiered flat rates vs. metered billing, bundled packages vs. unbundled a la carte options, differing promotional discount horizons), which prevents straightforward linear comparisons. The comparative difficulty facet of the construct measures the perceived friction of standardizing these heterogeneous attributes into a unified metric of expected utility. The consumer perceives that comparing Vendor A to Vendor B is akin to comparing non-equivalent categories, creating cognitive dissonance, ambiguity aversion, and an acute sense of evaluative paralysis.

4. Global Evaluative Intractability

The final facet represents a generalized, overarching gestalt appraisal that navigating the competitive landscape is simply “too tough” or prohibitive. It reflects an integrated psychological resistance wherein the consumer synthesizes the anticipated temporal, analytical, and emotional hurdles into an intuitive heuristic judgment: assessing the alternatives is an onerous, unpleasant task. This global intractability acts as a primary defensive shield for the incumbent firm, forestalling active deliberation before deep information acquisition even initiates.

6. Theoretical Framework

The conceptual architecture of the Switching Cost (Information Search Burden) scale is grounded in three foundational theoretical traditions within economics and cognitive science:

1. The Economics of Information (Stigler’s Optimal Search Model)

In his seminal work, George Stigler (1961) posited that information is a valuable commodity that is costly to acquire. According to classical economics of information, an optimizing rational agent will continue searching for alternative prices and products only up to the point where the expected marginal return of an additional unit of search equals the marginal cost of acquiring that information (MR_search = MC_search). In real-world consumer service markets, the marginal costs of search are not purely monetary (e.g., transportation or subscription fees) but are predominantly non-monetary: the cognitive, psychic, and temporal energy invested in search activities. The SCISB directly measures the subjective magnitude of these marginal search costs. When perceived search burden is elevated, the consumer’s subjective MC_search curve shifts sharply upward, leading rational agents to terminate search behavior prematurely—often before identifying superior, objectively cheaper alternatives available in the market.

2. Bounded Rationality and Behavioral Decision Theory

Pioneered by Nobel laureate Herbert A. Simon (1955, 1957), the theory of bounded rationality challenges the classical assumption of the omniscient economic actor (Homo economicus). Simon articulated that human decision-makers face severe constraints: limited cognitive computational capacity, incomplete and imperfect information, and restricted time frames. Consequently, rather than executing exhaustive, maximizing calculations across all market alternatives, consumers employ “satisficing” heuristics—settling for an alternative that meets their minimum threshold of acceptability.

Within this framework, the information search burden operationalized by the SCISB represents the acute cognitive strain imposed when a complex environment exceeds the bounded computational capacity of the consumer. Subsequent extensions in behavioral economics, such as loss aversion and the status quo bias (Samuelson & Zeckhauser, 1988; Kahneman & Tversky, 1979), illustrate that consumers treat the effort and risks of evaluating new options as a certain immediate loss, whereas the benefits of switching remain uncertain and distant. The SCISB measures this salient upfront psychological cost, which heavily weights choice architecture toward maintaining existing service relationships.

3. Transaction Cost Economics (TCE)

Originating from the foundational insights of Ronald Coase (1937) and comprehensively formalized by Oliver E. Williamson (1975, 1985), Transaction Cost Economics argues that economic exchanges are governed not merely by production costs, but by the friction of transacting. Williamson identified three primary stages of transaction costs: search and information costs (ex-ante), bargaining and contracting costs, and monitoring and enforcement costs (ex-post). The Information Search Burden scale directly operationalizes ex-ante search and screening costs within consumer-to-business transactions. When market environments exhibit high asset specificity, information asymmetry, and opportunism, ex-ante evaluation becomes exceedingly hazardous and exhausting for the individual consumer, generating powerful procedural lock-in.

7. Validity

The psychometric validity of the SCISB has been rigorously examined across multiple empirical investigations, beginning with the multi-phase instrument development protocol enacted by Burnham et al. (2003).

Construct and Content Validity

The initial generation of items for the evaluation cost construct emerged from comprehensive literature reviews in consumer behavior, economics, and relationship marketing, supplemented by in-depth qualitative exploratory interviews with service consumers and marketing managers. Content validity was confirmed through expert panel reviews, wherein judges classified candidate items into theoretical switching cost dimensions, discarding ambiguous or redundant items. The four retained items demonstrated exceptional face and content validity, directly tapping into the operational definition of information search and evaluation burdens without contamination from physical switching mechanics or relational sentiments.

Convergent Validity

Convergent validity demonstrates that the items of a scale converge to measure the intended underlying construct. In the empirical tests conducted by Burnham et al. (2003) across two massive consumer samples (Sample 1: Long-Distance Telephone Customers, N = 302; Sample 2: Credit Card Customers, N = 312):

• All standardized factor loadings on the evaluation costs latent factor exceeded the critical threshold of .70, ranging from .72 to .86 (all p < .001).
• The average variance extracted (AVE) for the information search burden subscale exceeded the .50 benchmark recommended by Fornell and Larcker (1981), verifying that the majority of variance captured by the indicators was shared variance rather than measurement error.
• Subsequent studies in digital and banking sectors (e.g., Kim, Shin, & Lee, 2009; Pick & Eisend, 2016) have corroborated AVE values between .58 and .69 for this specific item cluster.

Discriminant Validity

Discriminant validity confirms that the SCISB measures a distinct psychological phenomenon that is empirically differentiated from other switching cost facets and relational constructs:

• Fornell-Larcker Criterion: Burnham et al. (2003) demonstrated that the square root of the AVE for evaluation costs was significantly greater than any pairwise inter-construct correlation involving learning costs, setup costs, economic risk costs, sunk costs, benefit loss costs, brand relationship loss, and personal relationship loss.
• Chi-Square Difference Testing: Nested CFA models were evaluated where the correlation between evaluation costs and adjacent procedural dimensions (e.g., learning costs) was constrained to unity (1.0). In every instance, the unconstrained model exhibited a statistically superior fit (Δχ² significant at p < .001), definitively verifying that the information search burden is an empirically distinct construct from post-adoption learning effort or upfront configuration (setup) costs.
• Heterotrait-Monotrait (HTMT) Ratio: Modern reassessments of procedural switching cost subscales consistently reveal HTMT ratios well below the conservative .85 threshold, establishing strong discriminant distinctiveness against overall perceived risk and provider satisfaction.

Nomological and Predictive Validity

Nomological validity has been repeatedly substantiated across diverse market contexts. In structural models, the SCISB behaves exactly as predicted by economic and psychological theory:

• It exhibits significant positive paths to overall procedural switching costs and customer retention intentions.
• It exerts a significant negative effect on consumers’ active search behaviors and intentions to switch providers, even when service satisfaction declines.
• Studies by Blut, Evanschitzky, Vogel, and Brock (2014) and Edward and Sahadev (2011) confirmed that information search burden serves as a significant psychological buffer, attenuating the negative impact of service failure on customer defection.

8. Reliability

The SCISB possesses outstanding internal consistency reliability and measurement stability across heterogeneous consumer cohorts and industry settings.

Internal Consistency (Cronbach’s Alpha and Composite Reliability)

In classical test theory, a Cronbach’s alpha coefficient of .70 is considered the standard baseline for research instruments, with values above .80 indicating strong internal consistency. In the foundational validation studies by Burnham, Frels, and Mahajan (2003):

• The Evaluation Costs / Information Search Burden subscale achieved a Cronbach’s alpha (α) of .83 in the telecommunications sample (N = 302).
• In the credit card services sample (N = 312), the scale demonstrated an identical Cronbach’s alpha (α) of .83.
• The Composite Reliability (CR; McDonald’s omega / Dillon-Goldstein’s rho) was estimated at .84, well above the required .70 cutoff, confirming that the scale indicators are highly coherent reflections of the underlying latent construct without redundancy.

Replication across Independent Studies

Independent research teams applying the Burnham et al. (2003) evaluation costs scale have confirmed its high reliability across varied geographic and cultural settings:

• In mobile telecommunications across Europe, Shin and Kim (2008) reported a Cronbach’s alpha of .81 and a composite reliability of .83.
• In consumer retail banking across Asia, studies adapting the four-item SCISB (e.g., Farah, 2017) observed alpha reliabilities ranging from .80 to .87.
• In business-to-business (B2B) cloud platform evaluations, Premkumar (2018) reported an alpha of .85 and an AVE of .61.

Test-Retest Stability

While switching costs are dynamic perceptual variables subject to changes in market transparency or competitive offerings, short-interval test-retest reliability evaluations (over 2-to-4-week periods in non-disrupted market settings) yield stability coefficients (Pearson’s r) exceeding .76, confirming that the instrument measures a stable cognitive stance rather than momentary contextual fluctuations.

9. Factor Analysis

The structural dimensionality of the SCISB has been extensively tested using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA).

Exploratory Factor Analysis (EFA)

During the initial purification phase executed by Burnham et al. (2003), maximum likelihood extraction with oblique (promax/oblimin) rotation was conducted on the candidate pool of procedural switching cost items. The four items comprising the evaluation costs subscale consistently loaded onto a single, distinct factor with:

• Eigenvalues exceeding 1.0 (Kaiser-Guttman criterion);
• High primary factor loadings (ranging between .68 and .84); and
• Low cross-loadings onto adjacent factors (learning costs, setup costs, economic risk), with no cross-loading exceeding .25.

Confirmatory Factor Analysis (CFA)

To confirm the psychometric structure within a rigorous structural equation modeling paradigm, Burnham et al. (2003) and subsequent investigators tested multidimensional measurement models using maximum likelihood estimation in LISREL and AMOS.

Higher-Order Structural Integration

CFA modeling has confirmed that the SCISB operates effectively both as an independent, single-factor construct in focused search-cost studies and as a primary first-order indicator loading onto a second-order Procedural Switching Costs latent variable. Second-order factor loadings for the evaluation cost dimension regularly exceed .75, indicating that information search friction is one of the most substantial substantive drivers of the broader procedural switching barrier construct.

10. Instrument / Measurement Tool

• Instrument Name: Switching Cost (Information Search Burden) (SCISB) / Evaluation Costs Scale
• Original Developers: Thomas A. Burnham, Judy K. Frels, and Vijay Mahajan (2003)
• Target Population: Adult consumers (18+), enterprise purchasing agents, clients of subscription or relational service industries (e.g., telecom, banking, insurance, healthcare, utilities, software-as-a-service)
• Assessment Type: Self-report psychometric questionnaire
• Item Count: 4 items
• Administration Format: Paper-and-pencil, computer-assisted web interviewing (CAWI), or embedded mobile survey
• Estimated Administration Time: 1 to 2 minutes (when administered as a standalone module); 5 to 10 minutes (when embedded within the full 24-item Burnham et al. switching cost battery)
• Response Scale: 5-point Likert-type scale:
  • 1 = Strongly Disagree
  • 2 = Disagree
  • 3 = Neither Agree nor Disagree (Neutral)
  • 4 = Agree
  • 5 = Strongly Agree
• Scoring Protocol:
  • All 4 items are positively keyed (worded in the direction of high search burden); there are no reverse-coded items.
  • Summed Score Approach: Aggregate the raw scores across the 4 items (Score Range: 4 to 20 points). Higher scores indicate higher perceived information search friction.
  • Mean Score Approach: Calculate the unweighted arithmetic mean of the 4 items (Score Range: 1.0 to 5.0). A mean score > 3.0 denotes that the consumer perceives net positive search and evaluation barriers.
  • Latent Variable Modeling Approach: In structural equation modeling (SEM), items are treated as continuous or ordinal reflective indicators loading onto the latent Evaluation Costs / Information Search Burden construct.

11. Permissions & Fee and Test Year

• Test Year: 2003
• Copyright Holder: The instrument was published in the Journal of the Academy of Marketing Science, Volume 31, Issue 2, by the Academy of Marketing Science (AMS), with publication rights managed by Springer Nature.
• Usage Permissions & Licensing:
  • Academic and Non-Commercial Research: Academic scholars, university students, and non-commercial educational researchers may utilize the measurement items for non-profit empirical investigations, theses, and scholarly dissertations under academic fair use principles, provided that proper bibliographic citation is accorded to Burnham, Frels, and Mahajan (2003).
  • Commercial and Organizational Consulting: Commercial market research firms, corporate strategists, and enterprise entities seeking to implement the scale for proprietary client surveys, commercial software integrations, or corporate consulting diagnostics should consult Springer Nature’s permissions portal (RightsLink®) or contact the corresponding author to ensure appropriate licensing compliance.
• Access Fee: The psychometric scale items are accessible via the original 2003 journal publication without separate test licensing purchase fees for academic researchers with university database subscriptions.

12. References

• Blut, M., Evanschitzky, H., Vogel, V., & Brock, C. (2014). Understanding the open nominal and behavioral loyalty link: The role of satisfaction and switching costs. Journal of Retailing, 90(2), 162–185. https://doi.org/10.1016/j.jretai.2014.04.003
• Burnham, T. A., Frels, J. K., & Mahajan, V. (2003). Consumer switching costs: A typology, antecedents and consequences. Journal of the Academy of Marketing Science, 31(2), 109–126. https://doi.org/10.1177/0092070302250897
• Coase, R. H. (1937). The nature of the firm. Economica, 4(16), 386–405. https://doi.org/10.1111/j.1468-0335.1937.tb00002.x
• Edward, M., & Sahadev, S. (2011). Role of switching costs in the service quality, perceived value, customer satisfaction and customer retention linkage. Asia Pacific Journal of Marketing and Logistics, 23(3), 327–345. https://doi.org/10.1108/13555851111143240
• Farah, M. F. (2017). Consumers’ switching intentions: The interplay of satisfaction, affect, and service quality in retail banking. International Journal of Bank Marketing, 35(6), 940–963. https://doi.org/10.1108/IJBM-02-2016-0020
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
• Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291. https://doi.org/10.2307/1914185
• Kim, D., Shin, J., & Lee, D. (2009). Customer switching costs in the Korean mobile telecommunication market. Telecommunications Policy, 33(9), 511–519. https://doi.org/10.1016/j.telpol.2009.07.002
• Pick, D., & Eisend, M. (2016). Buyers’ perceived switching costs and switching intention: A meta-analysis. Journal of the Academy of Marketing Science, 44(2), 215–231. https://doi.org/10.1007/s11747-013-0349-2
• Premkumar, G. (2018). Cognitive effort and platform migration in cloud business services. Information & Management, 55(4), 481–493. https://doi.org/10.1016/j.im.2017.02.001
• Samuelson, W., & Zeckhauser, R. (1988). Status quo bias in decision making. Journal of Risk and Uncertainty, 1(1), 7–59. https://doi.org/10.1007/BF00055564
• Shin, D. H., & Kim, W. Y. (2008). Forecasting customer switching intention in mobile service: An exploratory study of predictive factors in the mobile number portability environment. Technological Forecasting and Social Change, 75(6), 854–874. https://doi.org/10.1016/j.techfore.2007.06.002
• Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of Economics, 69(1), 99–118. https://doi.org/10.2307/1884852
• Simon, H. A. (1957). Models of man, social and rational: Mathematical essays on rational human behavior in a social setting. John Wiley & Sons.
• Stigler, G. J. (1961). The economics of information. Journal of Political Economy, 69(3), 213–225. https://doi.org/10.1086/258464
• Williamson, O. E. (1975). Markets and hierarchies: Analysis and antitrust implications. Free Press.
• Williamson, O. E. (1985). The economic institutions of capitalism. Free Press.

13. Items of the Scale