Foundations of Design Thinking and Entrepreneurial Innovation

Introduction

Entrepreneurship is often described as the creation of new organizations, products, services, or business models under conditions of uncertainty. Yet entrepreneurial opportunity rarely appears as a fully defined problem with a known solution. Entrepreneurs must interpret incomplete information, understand people’s unarticulated needs, frame worthwhile problems, generate alternatives, and learn through action. Design thinking provides a disciplined approach to these activities.

Design thinking is not simply a set of brainstorming exercises. It is a human-centred approach to problem framing and innovation that combines empathy, experimentation, collaboration, visualisation, and iterative learning. It is particularly valuable when the problem is ambiguous, stakeholders have different interests, and evidence is limited. In such settings, conventional analysis alone may be insufficient because the central challenge is not merely to select the best answer, but to discover what the right question should be.

For entrepreneurs, design thinking supports opportunity recognition, customer understanding, value-proposition development, prototyping, and business-model innovation. For established organizations, it can help renew products, improve services, redesign internal processes, and challenge assumptions embedded in existing systems.

Learning Objectives

By the end of this chapter, the learner should be able to:

1. Explain the historical development and intellectual foundations of design thinking.
2. Define central concepts such as empathy, framing, ideation, prototyping, iteration, desirability, feasibility, and viability.
3. Distinguish design thinking from creativity, invention, systems thinking, lean startup, and conventional problem-solving.
4. Describe the mindsets and practices required for effective design-led innovation.
5. Apply design thinking to entrepreneurial opportunity development and organizational innovation.
6. Evaluate the benefits, limitations, ethical issues, and managerial implications of design thinking.

1. The Meaning and Scope of Design Thinking

Design thinking may be understood in three related ways.

First, it is a way of thinking. It treats problems as potentially reframable and regards knowledge as something developed through inquiry and experimentation rather than received passively.

Second, it is a way of working. It uses activities such as observation, interviews, journey mapping, sketching, prototyping, and user testing. These activities make assumptions visible and enable teams to learn before committing substantial resources.

Third, it is a way of organizing innovation. It encourages multidisciplinary teams, direct engagement with users, rapid feedback, and the integration of technical, economic, social, and experiential considerations.

A widely used representation describes design thinking through five overlapping activities: empathize, define, ideate, prototype, and test. These should not be interpreted as a rigid linear sequence. Teams may return from testing to definition, from prototyping to research, or from ideation to reframing. The model is best understood as a learning cycle.

The concept of design has a broad meaning. It includes the intentional shaping of products, services, experiences, processes, environments, and institutions. Consequently, design thinking can be applied to a mobile application, a public-health programme, a retail experience, a recruitment process, or a social enterprise.

2. Historical and Intellectual Foundations

2.1 Design as a professional activity

Industrial design developed as a distinct professional field during the industrial era, when products had to be produced at scale while remaining functional, safe, and attractive. Designers worked between engineering, manufacturing, commerce, and culture. Their role demonstrated that innovation involved more than technical performance; it also involved usability, meaning, appearance, and context.

2.2 Design research and design methods

During the twentieth century, scholars began studying how designers solve problems. Early design-methods research sought systematic procedures that could improve complex design work. However, researchers soon recognized that design problems differ from well-defined scientific problems. Design problems are often “wicked”: their boundaries are contested, stakeholders disagree about goals, and every proposed solution changes the situation itself.

The design-methods movement therefore shifted from the search for a universal algorithm toward a more reflective understanding of design practice. Designers were seen as framing situations, synthesizing diverse forms of information, and learning through making.

2.3 Influential contributors and institutions

Several thinkers contributed to the modern understanding of design thinking. Herbert Simon described designing as a process of changing existing situations into preferred ones and emphasized the importance of bounded rationality. Donald Schön examined reflective practice and showed how professionals learn by acting, observing consequences, and revising their understanding. Peter Rowe analysed design thinking in architecture and urban design. Later, design consultancies and educational institutions, including IDEO and Stanford’s d.school, popularized human-centred design as an approach accessible to managers, entrepreneurs, engineers, and social innovators.

Tim Brown presented design thinking as a collaborative, human-centred approach that integrates people’s needs, technological possibilities, and requirements for business success. This formulation helped connect professional design with organizational innovation.

2.4 Design thinking and entrepreneurship

Entrepreneurship and design thinking share an orientation toward action under uncertainty. Entrepreneurs construct opportunities through interaction with customers, partners, technologies, and institutions. Design thinkers similarly treat opportunities as explored and shaped rather than simply discovered.

This relationship does not mean that every entrepreneurial decision is a design-thinking activity. Financial analysis, regulatory compliance, operations management, and competitive strategy remain essential. Design thinking complements, rather than replaces, these disciplines.

3. Core Principles and Mindsets

3.1 Human-centredness

Human-centred design begins with the experiences, goals, constraints, and social contexts of people affected by an innovation. It does not mean satisfying every stated preference. Users may not be able to articulate latent needs, and other stakeholders—employees, communities, regulators, suppliers, and non-users—may also be affected.

Human-centredness requires attention to both what people say and what they do. Interviews reveal perceptions and language; observation reveals behaviour and workarounds. Ethical research also requires informed participation, respect for privacy, and sensitivity to vulnerable groups.

3.2 Empathy and perspective-taking

Empathy is the disciplined attempt to understand another person’s situation without assuming that one’s own experience is universal. It involves observing, listening, asking open questions, and identifying emotional, functional, and social dimensions of experience.

Empathy is not agreement, sympathy, or the collection of pleasing quotations. Its purpose is to improve the quality of problem framing and reduce premature assumptions.

3.3 Problem framing

A problem statement determines what is considered relevant evidence and what types of solutions appear possible. Compare the following:

• “How can we build a faster payment terminal?”
• “How can we help small retailers complete transactions with less interruption?”

The first statement presumes a technical solution. The second opens inquiry into connectivity, training, user confidence, transaction design, and alternative payment arrangements.

A strong design brief identifies the people involved, the context, the underlying need, the constraints, and the opportunity for improvement without prescribing a solution too early.

3.4 Divergence and convergence

Design work alternates between divergence and convergence. Divergence expands the field of possibilities by generating observations, interpretations, ideas, and prototypes. Convergence narrows the field by selecting, combining, prioritizing, and testing alternatives.

Excessive convergence produces predictable solutions. Excessive divergence produces an unmanageable number of ideas. Effective innovation requires movement between the two modes.

3.5 Learning through making

A prototype is a deliberate, limited representation of an idea created to learn. It may be a sketch, paper interface, role-play, storyboard, physical model, spreadsheet, landing page, or service simulation. A prototype is not necessarily a preliminary version intended for sale.

Making an idea tangible exposes assumptions that are difficult to discuss abstractly. It also enables stakeholders to respond to something concrete. The appropriate fidelity depends on the learning objective: a rough sketch may be best for testing structure, while a functional prototype may be needed to test performance.

3.6 Tolerance for ambiguity and failure

Design thinking requires the ability to act without complete information. Small, safe-to-fail experiments can reveal what users value, what they misunderstand, and what technical or operational obstacles exist. Failure is useful only when it produces learning and does not impose unacceptable harm or cost. The phrase “fail fast” must never be used to justify careless experimentation with safety, privacy, livelihoods, or dignity.

3.7 Collaboration and co-creation

Complex problems involve multiple forms of expertise. Effective design teams include relevant users and combine business, technical, behavioural, operational, and cultural perspectives. Co-creation does not mean that every participant has equal authority in every decision. It means that affected knowledge is included and that decision rights are made explicit.

4. A Working Design-Thinking Process

4.1 Empathize: investigate experiences

Research methods may include contextual interviews, participant observation, diary studies, stakeholder mapping, secondary research, and analysis of support requests or usage data. Researchers should distinguish observations from interpretations.

For example:

• Observation: a customer asks for assistance twice while completing an online form.
• Interpretation: the form may be difficult to understand or may create anxiety.
• Hypothesis: clearer language and progress information could reduce assistance requests.

This distinction prevents assumptions from being presented as facts.

4.2 Define: synthesize and frame

Definition involves organizing research into patterns and meaningful insights. Common tools include affinity mapping, personas, journey maps, ecosystem maps, and “How might we?” questions.

A useful opportunity statement usually includes a user or stakeholder, a need, and an important context. For example: “How might we help first-time entrepreneurs understand regulatory requirements without requiring expensive professional advice?”

Personas should be evidence-based and should not reduce people to stereotypes. Journey maps should show stages, actions, emotions, barriers, and opportunities. They are analytical devices, not substitutes for research.

4.3 Ideate: generate alternatives

Ideation techniques include brainstorming, brainwriting, analogy, forced connections, morphological analysis, role reversal, and concept combination. Effective ideation temporarily postpones judgement while maintaining a clear design challenge.

Ideas should subsequently be evaluated against relevant criteria. A common entrepreneurial lens considers:

• Desirability: Do people want or value it?
• Feasibility: Can it be developed and delivered with available or attainable capabilities?
• Viability: Can it create sufficient economic or organizational value to sustain itself?
• Responsibility: Are its effects ethically and socially acceptable?

These dimensions are related but distinct. A desirable solution may be technically impossible; a feasible solution may lack demand; a viable solution may create unacceptable social harm.

4.4 Prototype: externalize the concept

Prototyping should be guided by a question. Examples include:

A prototype should be no more elaborate than necessary to obtain useful evidence. Overbuilding before learning increases cost and creates emotional attachment to weak ideas.

4.5 Test: obtain evidence and revise

Testing is a structured learning activity, not a demonstration designed to obtain praise. Teams should define what they want to learn, identify appropriate participants, observe behaviour, ask neutral questions, and record evidence.

Testing can reveal three different outcomes: the concept may be supported, it may require modification, or the underlying assumption may be rejected. A negative result is valuable when it prevents larger investment in an undesirable or unsafe direction.

5. Distinguishing Design Thinking from Related Concepts

Creativity and design thinking

Creativity is the capacity to produce ideas that are novel and potentially useful. It can occur in art, science, advertising, engineering, or everyday life. Design thinking provides a context in which creativity is directed toward human and organizational needs and connected to testing.

Invention and innovation

An invention is a new technical or conceptual creation. Innovation is the successful introduction and adoption of a new or significantly improved product, process, service, or business model. A technically impressive invention may not become an innovation if it lacks users, an implementation pathway, or a sustainable value model.

Systems thinking

Systems thinking examines relationships, structures, feedback loops, delays, and unintended consequences. Design thinking may begin with an individual’s experience, but responsible innovation must also consider the broader system. For example, redesigning a food-delivery interface should include impacts on workers, restaurants, traffic, data use, and environmental waste.

Lean startup

Lean startup emphasizes explicit business hypotheses, minimum viable products, customer feedback, and decisions to persevere, pivot, or stop. Design thinking and lean startup differ in emphasis. Design thinking often explores needs and alternative frames before choosing a concept. Lean startup commonly tests whether a chosen business model has evidence of demand and economic potential. Both reject large unsupported commitments and value learning through experiments.

Conventional problem-solving

Conventional problem-solving works well when the problem, objective, constraints, and measures of success are reasonably stable. It may involve diagnosis, root-cause analysis, option evaluation, and implementation. Design thinking is especially useful when these elements are uncertain or contested. It does not replace rigorous analysis once a problem is sufficiently defined.

6. Design Thinking in Entrepreneurship

6.1 Opportunity recognition

Entrepreneurial opportunities may emerge from unmet needs, inconvenient workarounds, technological change, regulatory shifts, demographic trends, or contradictions in existing services. Design research helps entrepreneurs notice problems that market reports may overlook, particularly problems embedded in everyday routines.

6.2 Value proposition development

A value proposition explains who is served, what important problem or desire is addressed, how the offer creates value, and why the proposed approach may be preferable to alternatives. Interviews and prototypes help distinguish a genuine need from a merely interesting idea.

Entrepreneurs should avoid asking only whether users “like” a concept. More informative evidence includes changes in behaviour, willingness to invest time or money, repeated use, referrals, and actual adoption under realistic conditions.

6.3 Business-model innovation

Design thinking can be applied beyond products to channels, revenue models, partnerships, customer relationships, and key activities. A business model may be represented as a set of hypotheses rather than a fixed plan. Each hypothesis should be tested with evidence appropriate to its risk.

For example, a social enterprise may hypothesize that schools will pay for a digital learning service, that teachers will use it weekly, and that a trained facilitator can support implementation. These are different assumptions requiring different tests.

6.4 Resource constraints and effectuation

New ventures commonly operate with limited capital, incomplete information, and changing conditions. Design thinking supports affordable experimentation and helps entrepreneurs use available resources creatively. This complements effectual approaches to entrepreneurship, which emphasize starting with available means, forming partnerships, and allowing goals to develop through action.

7. Design Thinking in Established Organizations

Organizations use design thinking to improve customer experience, employee experience, service delivery, and strategic renewal. It can challenge the “dominant logic” through which an organization interprets customers and competitors.

However, organizational adoption is difficult. Existing performance measures may reward efficiency in current operations rather than exploration of new possibilities. Hierarchical decision-making may discourage frontline knowledge. Departments may protect information, and leaders may demand predictable returns before uncertainty has been reduced.

Successful implementation generally requires:

1. Senior sponsorship without excessive control.
2. Access to users and frontline employees.
3. Multidisciplinary teams with clear decision rights.
4. Time and resources for research and experimentation.
5. A portfolio of experiments rather than dependence on one idea.
6. Evaluation criteria appropriate to the stage of innovation.
7. Integration with operations, finance, technology, legal, and risk functions.

Design thinking should not become a superficial workshop label. Its credibility depends on whether research changes decisions and whether prototypes influence investment and implementation.

8. Illustrative Case: Redesigning Access to Small-Business Finance

This is a fictional illustrative case designed to demonstrate the application of design thinking.

Background

A regional financial institution observed that many micro-enterprise owners opened loan applications but failed to complete them. Management initially concluded that applicants needed a faster online form.

Problem

The stated problem—slow form completion—did not explain why applicants abandoned the process. The institution formed a multidisciplinary team including a relationship manager, a product designer, a compliance officer, a data analyst, and two small-business owners.

Analysis

The team observed applicants completing forms in their shops and conducted interviews at different times of day. Several patterns emerged. Applicants were uncertain about financial terminology, lacked some documents at the time of application, feared making a mistake, and did not know how long approval would take. The problem was therefore not simply interface speed; it involved confidence, preparation, transparency, and workflow design.

The team reframed the opportunity as follows: “How might we help time-constrained business owners understand their financing options and complete an application with confidence?”

Approach and solution

The team developed three prototypes:

1. A plain-language eligibility guide.
2. A document-preparation checklist delivered through a messaging service.
3. A staged application process showing progress and offering access to human assistance.

Applicants were invited to use paper mock-ups and later a low-fidelity digital prototype. Testing showed that users preferred the checklist and progress information, but some misunderstood the term “pre-approval.” The team revised the language and involved compliance specialists before conducting a limited pilot.

Outcome

The pilot did not immediately produce a complete digital transformation. It did, however, reduce avoidable confusion, identify documentation barriers, and improve the handoff between digital and human support. The institution then invested in a redesigned service rather than merely speeding up the original form.

Learning points

The case illustrates five principles. First, the initial problem statement may be too narrow. Second, observation can reveal barriers that users do not state directly. Third, prototypes make assumptions testable. Fourth, compliance and user experience must be addressed together. Fifth, design thinking produces better decisions when it is connected to implementation and measurable outcomes.

9. Evaluation, Evidence, and Metrics

Design thinking is sometimes criticized for relying on intuition. This criticism is justified when teams treat empathy or ideation as substitutes for evidence. Rigorous design practice uses qualitative and quantitative evidence at appropriate stages.

Early research may emphasize depth rather than statistical representativeness. A small number of carefully selected observations can reveal workflow problems, language barriers, or unmet needs. Later stages may require larger samples, controlled comparisons, usage analytics, financial modelling, or operational pilots.

Useful measures may include:

• task completion and error rates;
• time required to complete a process;
• adoption, retention, and repeat use;
• customer or employee effort;
• conversion or payment behaviour;
• cost to serve and operational reliability;
• accessibility and inclusion outcomes;
• environmental and social effects.

No single metric proves that an innovation is successful. Metrics must be interpreted in relation to the intended outcome and the stage of development.

10. Limitations and Critical Perspectives

Design thinking has important limitations.

First, it can oversimplify structural problems. A workshop cannot by itself resolve poverty, discrimination, weak institutions, or unequal access to power. Human-centred methods should be combined with policy, economic, legal, and systems analysis.

Second, users are not always the only or best source of direction. People may lack access to future technologies, may be constrained by current choices, or may express preferences that conflict with public safety or long-term welfare.

Third, the language of empathy can conceal power differences. Organizations may collect personal stories without giving participants influence over decisions. Participation should therefore include transparency, consent, fair compensation where appropriate, and feedback about how contributions were used.

Fourth, rapid iteration can privilege what is easy to prototype. Intangible, long-term, infrastructural, or preventive innovations may require slower research and institutional change.

Fifth, design thinking can be reduced to a branded process. Labels such as “empathize” and “ideate” have little value if teams do not conduct serious inquiry, make assumptions explicit, and accept evidence that challenges senior preferences.

11. Ethics, Governance, Technology, and AI

Designing an offering creates responsibilities toward direct users and affected non-users. Ethical review should consider privacy, accessibility, safety, discrimination, manipulation, labour conditions, environmental impact, and the distribution of benefits and harms.

Digital products require particular attention to data minimization, informed consent, cybersecurity, explainability, and meaningful human oversight. Personalization systems may improve relevance while also reinforcing exclusion or surveillance.

Artificial intelligence can support design research by summarizing interviews, generating alternative concepts, creating synthetic scenarios, or producing prototype content. These uses require caution. AI-generated summaries may omit minority perspectives, reproduce bias, or invent evidence. Sensitive data should not be entered into systems without appropriate authorization. Human researchers remain responsible for validating findings, protecting participants, and making consequential decisions.

A useful governance principle is to treat AI as an assistive tool for exploration rather than an unquestioned authority. Teams should document data sources, assumptions, model limitations, review procedures, and accountability for outcomes.

12. Best Practices for Entrepreneurial Design Thinking

1. Begin with a situation and affected people, not with a preferred technology.
2. Separate observations, interpretations, assumptions, and decisions.
3. Include diverse users and stakeholders, especially those likely to be overlooked.
4. Frame several possible problems before selecting one.
5. Generate alternatives before evaluating them.
6. Prototype the riskiest assumption as cheaply and safely as possible.
7. Use behavioural evidence rather than relying only on stated enthusiasm.
8. Involve technical, financial, operational, legal, and ethical expertise early enough to matter.
9. Record what was learned and how it changed the concept.
10. Define criteria for continuing, modifying, pivoting, or stopping.
11. Protect participant dignity, privacy, safety, and agency.
12. Connect experimentation to a realistic implementation and business model.

Chapter Summary

Design thinking is a human-centred, iterative approach to addressing ambiguous problems and creating valuable change. Its intellectual roots include design practice, design-methods research, bounded rationality, and reflective practice. Its common activities—empathize, define, ideate, prototype, and test—form a flexible learning cycle rather than a rigid sequence.

The approach depends on problem framing, perspective-taking, divergence and convergence, learning through making, collaboration, and responsible experimentation. It differs from creativity because it connects ideas to human needs and testing; from invention because it includes services and systems; from systems thinking because it places stronger emphasis on lived experience and prototyping; from lean startup because it often explores needs and frames before testing business hypotheses; and from conventional problem-solving because it is especially suited to uncertain or poorly defined problems.

For entrepreneurs, design thinking supports opportunity recognition, value-proposition development, business-model innovation, and evidence-based learning. In established organizations, it can improve services and challenge entrenched assumptions. Its limitations include possible oversimplification, superficial participation, prototype bias, and misuse as a fashionable workshop process. Ethical practice requires attention to power, privacy, inclusion, safety, sustainability, and accountability, including when AI tools are used.

Key Terms

Design thinking: A human-centred and iterative approach to framing and addressing complex problems.

Human-centred design: Designing with serious attention to people’s experiences, needs, capabilities, and contexts.

Empathy: Disciplined understanding of another person’s perspective and situation.

Problem framing: Defining how a situation, need, opportunity, and constraints will be understood.

Wicked problem: A complex problem with contested boundaries, interacting causes, and no single agreed solution.

Ideation: Deliberate generation and development of multiple possible concepts.

Divergence: Expanding the range of observations, interpretations, or possible solutions.

Convergence: Narrowing and prioritizing alternatives using explicit criteria.

Prototype: A limited representation of an idea created for learning or testing.

Iteration: Repeated cycles of action, feedback, reflection, and revision.

Desirability: The extent to which people value or want a proposed solution.

Feasibility: The extent to which a solution can be developed and delivered.

Viability: The extent to which a solution can be economically or organizationally sustained.

Innovation: Successful adoption or implementation of a new or significantly improved offering or method.

Invention: A novel technical, conceptual, or functional creation.

Lean startup: An approach emphasizing hypotheses, experiments, validated learning, and business-model adaptation.

Systems thinking: Analysis of relationships, feedback, interdependence, and wider consequences within a system.

Co-creation: Collaborative development of value or solutions with relevant users and stakeholders.

Reflective practice: Learning by acting, examining consequences, and revising professional understanding.

Value proposition: An explanation of who is served, what value is created, and why an offer is relevant.

Review Questions

Short Answer Questions

1. What is meant by human-centred design?
2. Why is problem framing important in design thinking?
3. Distinguish desirability, feasibility, and viability.
4. What is the purpose of a prototype?
5. State two differences between design thinking and conventional problem-solving.

Long Answer Questions

1. Explain the historical and intellectual foundations of design thinking.
2. Discuss the five commonly used activities in the design-thinking process and explain why they are not strictly linear.
3. Compare design thinking with lean startup and systems thinking.
4. Explain how design thinking supports entrepreneurial opportunity recognition and business-model innovation.
5. Critically evaluate the limitations and ethical risks of design thinking in organizations.

Analytical / Application Questions

1. A university observes that many students abandon an online scholarship application. Develop an initial design-thinking plan, including research activities, a reframed opportunity statement, prototype choices, and evidence for evaluation.
2. An entrepreneur wants to launch an AI-based hiring platform. Identify at least five assumptions that should be tested and explain the ethical safeguards required.
3. A manufacturer has created a technically superior reusable water bottle, but customers are not buying it. Use the concepts of desirability, feasibility, viability, and problem framing to analyse the situation and recommend next steps.

Multiple Choice Questions with Answers

Question 1

Which statement best describes design thinking?

A. A strictly linear method for solving technical problems

B. A human-centred and iterative approach to framing and addressing problems

C. A financial technique for valuing new ventures

D. A manufacturing system focused only on efficiency

Correct Answer: B. A human-centred and iterative approach to framing and addressing problems

Question 2

What is the primary purpose of problem framing?

A. To select a final product before research begins

B. To eliminate the need for user involvement

C. To define how a situation and opportunity will be understood

D. To calculate the cost of production

Correct Answer: C. To define how a situation and opportunity will be understood

Question 3

Which activity is most directly associated with divergence?

A. Generating a wide range of possible concepts

B. Selecting one supplier

C. Approving a final budget

D. Closing a project

Correct Answer: A. Generating a wide range of possible concepts

Question 4

A prototype is best understood as:

A. A completed product ready for mass production

B. A limited representation created to generate learning

C. A legal contract with a customer

D. A substitute for market research in every situation

Correct Answer: B. A limited representation created to generate learning

Question 5

Which criterion asks whether people value or want a proposed solution?

A. Feasibility

B. Viability

C. Desirability

D. Compliance

Correct Answer: C. Desirability

Question 6

How does design thinking generally differ from conventional problem-solving?

A. It avoids all forms of analysis

B. It focuses more on discovering and reframing uncertain problems

C. It never uses evidence

D. It requires every problem to have a technical solution

Correct Answer: B. It focuses more on discovering and reframing uncertain problems

Question 7

Which statement best distinguishes invention from innovation?

A. Invention is always commercially successful, whereas innovation is not

B. Innovation concerns successful adoption or implementation, while invention concerns a novel creation

C. Invention applies only to services, whereas innovation applies only to machines

D. The terms are identical in all contexts

Correct Answer: B. Innovation concerns successful adoption or implementation, while invention concerns a novel creation

Question 8

What is a central emphasis of lean startup?

A. Validated learning through business experiments

B. Avoiding all customer contact until launch

C. Replacing prototypes with long-term forecasts

D. Maximizing organizational hierarchy

Correct Answer: A. Validated learning through business experiments

Question 9

Which practice is most ethically appropriate when using AI to summarize interviews?

A. Accepting every generated summary without review

B. Entering any sensitive data into a public tool

C. Validating summaries and protecting participant privacy

D. Removing human accountability from the process

Correct Answer: C. Validating summaries and protecting participant privacy

Question 10

A solution is technically possible and customers want it, but the venture cannot sustain its costs. Which dimension is weakest?

A. Desirability

B. Feasibility

C. Viability

D. Empathy

Correct Answer: C. Viability