Innovation, Entrepreneurship and the Future of Media

Introduction

Media organizations operate in an environment in which technology, audience behavior, regulation and business models change simultaneously. The competitive advantage of a newspaper, broadcaster, streaming service, podcast network or creator-led venture can disappear when audiences migrate to a new platform, advertising shifts to another format, or artificial intelligence changes the cost of production. Consequently, media management is no longer concerned only with operating established products efficiently. It also requires the ability to identify opportunities, test assumptions, allocate scarce resources and prepare for uncertain futures.

Innovation is not synonymous with new technology. It is the successful implementation of a new or significantly improved product, process, organizational practice or business model that creates value. Entrepreneurship is the process of recognizing and pursuing opportunities under conditions of uncertainty, often by assembling resources that are not yet fully controlled. In media, these activities may involve launching a niche publication, developing a subscription product, creating an interactive documentary, building a community around a creator, or redesigning a legacy newsroom.

This chapter integrates four managerial capabilities: design thinking, lean experimentation, scenario planning and venture strategy. It then applies them to the creator economy, immersive media, decentralized technologies, artificial intelligence and changing audience behavior. The central argument is that future-oriented media management must combine imagination with disciplined evidence, commercial judgment with public responsibility, and technological ambition with audience trust.

Learning Objectives

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

1. Distinguish innovation, entrepreneurship and digital transformation in media.
2. Apply design thinking to identify audience problems and formulate media opportunities.
3. Construct a lean experiment and interpret evidence without confusing activity with validation.
4. Use unit economics and innovation metrics to evaluate a media venture.
5. Explain the opportunities and risks of creator economies, immersive media and decentralized technologies.
6. Develop alternative scenarios and use them in strategic planning.
7. Produce an integrated media venture or innovation plan that addresses value, viability, feasibility, ethics and governance.

1. Innovation and Entrepreneurship in Media

1.1 Innovation as value creation

A useful distinction is between invention and innovation. Invention produces a new idea or artifact; innovation occurs when that idea is implemented and adopted. A newsroom may invent an augmented-reality prototype, but it has innovated only if audiences use it, the organization can sustain it and it produces meaningful editorial, social or economic value.

Media innovation can be classified in several ways:

Innovation may be incremental, such as improving a recommendation interface, or radical, such as moving from scheduled broadcasting to on-demand streaming. It may also be sustaining, improving an existing market, or disruptive, initially serving a smaller or overlooked audience before challenging established providers. The term “disruptive” should be used carefully: not every successful digital product is disruptive in the strict strategic sense.

1.2 Entrepreneurship under uncertainty

Entrepreneurial decisions differ from routine management decisions because the relevant information does not yet exist. A manager may optimize a known production process; an entrepreneur tests whether a new audience, need or revenue mechanism exists at all. Media entrepreneurs therefore work with hypotheses about users, content, distribution, willingness to pay and institutional legitimacy.

Entrepreneurship can occur inside or outside an established organization. Intrapreneurship describes entrepreneurial activity by employees who develop new initiatives within an existing media company. Corporate structures provide resources, brands and infrastructure, but they may also create approval delays, risk aversion and conflicts with existing revenue streams. Independent ventures have greater autonomy but usually face severe resource constraints.

A media opportunity is stronger when it satisfies four tests:

• Desirability: a recognizable audience problem or aspiration exists.
• Feasibility: the organization can produce and distribute the proposed solution.
• Viability: revenue, funding or institutional support can sustain it.
• Responsibility: the venture is lawful, trustworthy and socially defensible.

These tests are interdependent. A highly desirable product that cannot be delivered reliably is not a viable venture. A profitable product that exploits vulnerable users may create regulatory, reputational and ethical liabilities.

2. Design Thinking for Media Ventures

Design thinking is a human-centered approach to innovation. It treats audience needs as a starting point while recognizing that users may not be able to state their needs directly. The commonly used cycle consists of empathize, define, ideate, prototype and test. In practice, the process is iterative rather than linear.

Empathize

Media managers gather evidence through interviews, observation, diary studies, usability tests, analytics and community engagement. The aim is not to collect flattering opinions about an idea. It is to understand context: when people consume media, what barriers they face, whom they trust, what alternatives they use and what emotional or practical outcomes they seek.

Researchers must distinguish what people say from what they do. A participant may claim that they want long-form investigative content but rarely complete articles longer than five minutes. This does not make the interview useless; it indicates a need to examine trade-offs, contexts and actual behavior.

Define

Research findings should be synthesized into a specific problem statement. A useful format is: “A defined audience needs a way to achieve a particular outcome because an observed barrier prevents it.” For example: “Commuting nurses need a reliable way to understand local health-policy changes because their work schedules make conventional evening broadcasts inaccessible.”

A problem statement should avoid embedding the solution. “Nurses need a podcast” prematurely selects a format; “nurses need accessible, trustworthy briefings during irregular schedules” leaves room for audio, text, alerts or other solutions.

Ideate and prototype

Teams generate multiple responses before selecting one. Prototypes may include a paper interface, sample episode, landing page, clickable mock-up, editorial workflow or manually delivered service. A prototype is not merely a miniature final product. It is an instrument for learning about a particular uncertainty.

A prototype should therefore be accompanied by a learning question, such as: “Will users understand the difference between a reported fact and an expert interpretation?” or “Will paying members value access to a moderated discussion more than additional articles?”

Test and iterate

Testing should involve representative users and observable tasks. Useful evidence includes completion rates, comprehension, retention, repeat use, conversion behavior and qualitative explanations. The team then decides whether to persevere, modify the proposition or stop the experiment. Iteration is not an excuse to ignore negative findings; it is a disciplined response to them.

3. Lean Experimentation and Media Metrics

Lean experimentation applies scientific reasoning to venture development. The team states a hypothesis, identifies a measurable test, defines a threshold for success and records the result. This prevents organizations from investing heavily in untested assumptions.

A hypothesis should identify a target audience, proposed value and expected behavior. For example: “Among urban university students, a weekly five-minute audio explainer will achieve at least 40% episode completion and produce a 5% registration rate from qualified visitors within four weeks.” The thresholds are not universal truths; they are decision rules established before observing the result.

The minimum viable product

A minimum viable product (MVP) is the smallest version of an offering that can generate meaningful learning from real or realistically simulated use. It is not necessarily a low-quality product. In journalism, accuracy, safety and fairness are not optional features that may be removed from an MVP. The team may reduce scope while preserving professional standards.

Examples include:

• a manually curated newsletter before building recommendation software;
• a limited podcast season before commissioning a permanent studio;
• a paid pilot with one community before national expansion;
• a moderated online event before constructing a large membership platform.

Metrics and unit economics

Media teams often report vanity metrics such as impressions, followers or downloads. These may be useful descriptive indicators but do not necessarily demonstrate value. More decision-relevant metrics include active users, completion, retention, conversion, contribution margin, referral rate, trust and correction rates.

A basic conversion rate is:

The numerator and denominator must refer to the same period and audience definition. For example, if 240 of 6,000 eligible visitors subscribe, the conversion rate is 4%.

For a subscription product, monthly contribution margin per subscriber can be estimated as:

Here, price and variable cost must be measured over the same period and in the same currency. Variable costs may include payment processing, delivery, usage-based software and content costs that change with subscriber volume. Fixed salaries and rent are excluded from contribution margin but remain relevant to total profitability.

A simplified customer acquisition payback period is:

The result is measured in months when both inputs are monthly monetary values. This estimate assumes stable contribution margin, ignores discounting and churn, and should not be treated as a complete lifetime-value model.

For example, if acquisition costs $18 per subscriber and monthly contribution margin is $6, payback occurs in 3 months. If many subscribers cancel before three months, the apparent payback is misleading; retention and cohort analysis are required.

A practical experiment dashboard should combine four categories:

Metrics must be interpreted in context. High engagement can result from outrage or accidental autoplay rather than meaningful value. A low conversion rate may reflect poor pricing, weak trust, unsuitable timing or an audience that values the content but cannot pay.

4. Business Models and the Creator Economy

The creator economy consists of individuals and small teams producing media and monetizing attention, expertise, community or intellectual property through platforms and direct relationships. Revenue sources include advertising shares, sponsorship, subscriptions, memberships, commerce, licensing, live events, commissions and fan funding.

Creators benefit from low-cost production and direct audience access. They can experiment rapidly, develop distinctive voices and serve niche communities overlooked by mass media. However, platform dependence creates significant vulnerabilities. Algorithmic changes, account suspension, changing revenue shares and audience fragmentation can undermine income without warning. A creator’s personal identity may also become inseparable from the brand, producing burnout and reputational risk.

Media managers should assess creator ventures across five dimensions:

1. Audience ownership: Is the relationship mediated entirely by a platform, or does the creator hold consent-based email, membership or customer data?
2. Revenue diversity: Does income depend on one sponsor, platform or client?
3. Operational capacity: Can production, moderation, accounting and legal compliance be sustained?
4. Editorial independence: Are sponsorships and commercial incentives disclosed clearly?
5. Succession and resilience: Can the venture survive illness, controversy, departure or platform failure?

The creator economy also changes the meaning of employment. Freelancers may enjoy autonomy but lack stable income, benefits and bargaining power. Platforms and media firms should address fair contracts, transparent revenue sharing, intellectual-property rights, safety and procedures for appeals.

5. Immersive Media and Decentralized Technologies

Immersive media

Immersive media includes virtual reality, augmented reality, mixed reality, spatial audio and interactive environments. Its value is strongest when presence, spatial understanding or embodied participation improves the communication task. A virtual reconstruction may help audiences understand a historical site; an augmented layer may support live cultural interpretation; spatial audio may create a more accessible experience for some users.

Immersion is not automatically superior to conventional video or text. Hardware cost, motion sickness, accessibility, production expense, privacy and limited audience reach may outweigh benefits. Managers should ask:

• What comprehension or emotional outcome requires spatial or interactive treatment?
• Can the audience access the necessary device and bandwidth?
• Are alternative formats available?
• What biometric, location or behavioral data are collected?
• Could simulation create false realism or emotional manipulation?

Immersive journalism requires especially careful labeling. A reconstructed scene, synthetic voice or simulated perspective must not be presented as direct documentary evidence.

Decentralized technologies

Blockchain and related decentralized systems use distributed records and cryptographic verification. Potential media applications include rights registries, programmable royalties, digital collectibles, decentralized identity and community governance. Smart contracts are software instructions that execute specified actions when coded conditions are met; they are not automatically equivalent to legally enforceable contracts.

Decentralization may reduce dependence on a single intermediary, but it does not eliminate governance. Questions remain about who controls software upgrades, resolves disputes, corrects errors, protects personal data and pays transaction costs. Permanent records can conflict with privacy rights, and token ownership does not necessarily establish copyright ownership.

A responsible evaluation should distinguish:

• the problem to be solved;
• the specific function requiring a distributed ledger;
• the costs and energy implications of the chosen system;
• legal status of tokens or digital assets;
• consumer protection and fraud risks;
• accessibility for users without technical expertise.

Using a blockchain merely because it is fashionable is poor innovation management. A conventional database may be cheaper, faster and easier to govern when a trusted organization already controls the system.

6. Artificial Intelligence and the Future of Media Work

Artificial intelligence can assist research, transcription, translation, personalization, moderation, production planning and audience analysis. Generative systems can produce text, images, audio or video, but their output may contain fabricated claims, biased representations, copyright conflicts or undisclosed synthetic elements.

AI adoption should follow a risk-based approach. Low-risk uses, such as formatting a transcript for human review, differ from high-risk uses, such as automatically ranking political news, identifying alleged criminals or generating health advice. Human accountability remains necessary for editorial judgment, source verification, consent, correction and appeals.

A media organization should maintain an AI policy covering:

• approved and prohibited uses;
• disclosure of synthetic or substantially automated content;
• verification and source documentation;
• protection of confidential and personal data;
• copyright and licensing;
• bias testing and accessibility;
• human review and escalation;
• records of system versions and editorial decisions.

The strategic issue is not whether AI replaces all media workers. It is how tasks, skills and authority are redistributed. Demand may increase for prompt design, data literacy, verification, product management, computational storytelling and media ethics, while routine production tasks may decline. Managers must invest in reskilling rather than treating labor displacement as a purely technical consequence.

7. Scenario Planning for Uncertain Futures

Forecasting attempts to predict a likely future; scenario planning develops several plausible futures to test the robustness of strategy. It is especially useful when uncertainty is high and decisions have long-term consequences.

A scenario process typically includes:

1. Define the focal question and time horizon.
2. Identify trends already shaping the environment.
3. List critical uncertainties, such as regulation, platform access, audience payment or technology adoption.
4. Select two high-impact uncertainties and construct contrasting axes.
5. Develop a small number of coherent scenarios.
6. Test the proposed strategy in each scenario.
7. Identify signposts that indicate which future may be emerging.
8. Choose actions that are robust, options that preserve flexibility and experiments that generate information.

Consider a media venture planning for five years. One uncertainty is the degree of platform concentration; another is the willingness of audiences to pay for trusted information. A scenario matrix could produce: “Open and Paying,” “Open but Price-Sensitive,” “Platform-Controlled and Paying,” and “Platform-Controlled and Price-Sensitive.” Each scenario should include implications for distribution, data ownership, costs, staffing, regulation and editorial independence.

Scenarios are not predictions and should not be presented as probabilities unless a defensible forecasting method is used. Their value lies in exposing assumptions and preventing a single-point strategy.

8. Integrated Venture Planning

A media venture plan connects audience insight to operational and financial decisions. A concise plan should include:

• Purpose: the public, cultural or market problem addressed.
• Audience: primary users, needs, contexts and excluded groups.
• Value proposition: the specific benefit and reason to choose this offering.
• Editorial or creative proposition: what will be made and according to what standards.
• Distribution: owned channels, platforms, partnerships and accessibility formats.
• Revenue logic: subscriptions, advertising, sponsorship, grants, commerce or mixed income.
• Capabilities: people, technology, rights, data and partnerships required.
• Experiment roadmap: assumptions, tests, thresholds and decision dates.
• Scenario resilience: adaptations under alternative futures.
• Governance: privacy, safety, moderation, corrections, transparency and accountability.
• Financial controls: budget, cash runway, unit economics and investment gates.

A useful governance principle is “minimum necessary data.” Collect only information required for a defined purpose, retain it for a justified period and provide understandable consent and withdrawal mechanisms. Personalization should not become covert manipulation. Recommendation systems should be evaluated for discrimination, filter bubbles and incentives to maximize sensational engagement.

Illustrative integrated case: Civic Signals

Background. Civic Signals is a fictional, early-stage venture proposed by three media graduates. It aims to help residents understand local council decisions through short explainers, searchable documents and moderated community questions.

Problem. Existing council information is legally complete but difficult to navigate. Local newspapers have reduced staffing, while social-media discussions are active but often inaccurate. Interviews with residents indicate demand for trustworthy summaries, but limited willingness to pay for another general news subscription.

Analysis. The team maps the audience journey and identifies two initial segments: residents who want practical information about services, and civic organizations that need reliable monitoring. The team avoids assuming that a mobile application is necessary. Its first hypotheses are that users will return for decision alerts and that organizations will pay for structured monitoring.

Approach and solution. The MVP is a weekly email briefing and searchable web page produced manually for one council area. Each item links to primary documents, identifies uncertainty and provides a correction channel. A four-week experiment measures qualified registrations, alert opt-ins, repeat opening, question submissions and interviews with organizational users. The team tests a small institutional subscription rather than placing all content behind a paywall.

Suppose 2,000 qualified visitors produce 120 registrations. The registration rate is 6%, calculated as 120 ÷ 2,000 × 100. Of 120 registrants, 48 opt into alerts, producing an opt-in rate of 40% among registrants. These results suggest interest but do not prove sustainable demand. The team must examine whether users return, whether alerts are useful and whether institutions renew.

Outcome. In this illustrative case, the pilot shows strong demand for service-related alerts but weak demand for general political commentary. Two civic organizations agree to paid trials, while residents request an audio version. The team narrows the editorial proposition toward practical accountability information, introduces an accessible audio summary and postpones expensive automated document analysis.

Learning points. The case demonstrates problem-led design, a small MVP, explicit metrics, segmentation and disciplined refusal to overbuild technology. It also shows that public-interest media may require a mixed model combining institutional income, grants and selective audience contributions. Trust practices—source links, corrections and clear labeling—are part of the product, not merely compliance obligations.

9. Challenges, Ethics and Limitations

Innovation can reproduce inequalities. Digital products may exclude people with disabilities, low bandwidth, limited literacy or inadequate devices. Data-driven personalization can discriminate against groups represented poorly in training data. Creator systems can encourage unpaid labor and precarious employment. Immersive experiences may collect sensitive behavioral data, while decentralized systems may make harmful information difficult to remove.

Important ethical principles include autonomy, fairness, accountability, transparency, privacy, safety and proportionality. These principles may conflict. Full personalization can improve relevance but require more data; open participation can increase diversity but also harassment; permanent archives can preserve history but threaten privacy. Ethical management therefore requires documented trade-offs, affected-community consultation and review over time.

Regulatory obligations vary by jurisdiction but commonly concern privacy and data protection, consumer rights, advertising disclosure, copyright, employment, accessibility, competition, child safety and platform accountability. Managers should obtain specialist legal advice for high-risk launches rather than treating compliance as a final checklist.

Innovation methods also have limitations. Design thinking can become superficial if empathy is reduced to a few interviews. Lean metrics can privilege measurable short-term behavior over long-term civic value. Scenario planning can create attractive stories without changing decisions. Entrepreneurial rhetoric can shift risk from institutions to workers. These limitations are addressed through methodological discipline, diverse evidence, independent review and explicit public-interest criteria.

10. Best Practices for Media Innovation Managers

1. Start with a significant audience or public problem, not a fashionable technology.
2. State assumptions explicitly and rank them by uncertainty and consequence.
3. Build the smallest credible test, while never compromising accuracy, safety or rights.
4. Define success thresholds before observing results.
5. Combine behavioral data with interviews and contextual research.
6. Separate reach, engagement, conversion, quality and impact metrics.
7. Protect direct audience relationships and avoid dependence on one platform.
8. Design accessibility, privacy and disclosure into the product from the beginning.
9. Use scenarios to test strategy, not to create confident predictions.
10. Establish investment gates: continue, revise, pause or stop.
11. Document editorial, algorithmic and commercial decisions.
12. Treat trust, correction and accountability as sources of long-term value.

Chapter Summary

Innovation in media is the implementation and adoption of new products, processes, organizational practices or business models that create value. Entrepreneurship manages opportunity under uncertainty and may occur in independent ventures or established organizations. Strong opportunities satisfy desirability, feasibility, viability and responsibility tests.

Design thinking provides a human-centered cycle of empathizing, defining, ideating, prototyping and testing. Lean experimentation converts assumptions into measurable hypotheses and uses MVPs, decision thresholds and relevant metrics. Conversion rate, contribution margin and payback period can support financial reasoning, but they must be interpreted with retention, quality and trust evidence.

The creator economy expands opportunities for niche and personality-led media while exposing workers to platform dependence and precarious income. Immersive media is valuable when spatial or embodied experience improves understanding; decentralized technologies require careful evaluation of governance, privacy, legal status and actual need. Artificial intelligence can improve media work but demands verification, disclosure, data protection and human accountability.

Scenario planning helps managers explore plausible futures shaped by uncertainties such as platform concentration, regulation and willingness to pay. An integrated venture plan links purpose, audience, value proposition, editorial standards, distribution, revenue, capabilities, experiments, scenarios and governance. The most resilient media ventures combine technological experimentation with financial discipline, inclusion, ethical responsibility and durable audience trust.

Key Terms

Innovation: Implementation and adoption of a new or significantly improved offering, process, practice or business model.

Entrepreneurship: Recognition and pursuit of opportunities under uncertainty through the assembly of resources.

Intrapreneurship: Entrepreneurial activity undertaken within an established organization.

Design thinking: A human-centered, iterative approach to solving problems through research, ideation, prototyping and testing.

Value proposition: The specific benefit an offering promises to a defined audience.

Minimum viable product: The smallest credible offering that generates meaningful learning from use.

Lean experimentation: Hypothesis-driven testing used to reduce uncertainty before major investment.

Conversion rate: The percentage of an eligible audience completing a defined desired action.

Contribution margin: Revenue remaining after variable costs, available to cover fixed costs and profit.

Customer acquisition cost: The average cost of obtaining a customer or subscriber.

Creator economy: A media environment in which individuals or small teams produce content and monetize audiences, expertise or communities.

Immersive media: Media that creates interactive, spatial or embodied experiences through technologies such as VR, AR and spatial audio.

Decentralization: Distribution of control, records or decision-making across multiple participants rather than one central authority.

Smart contract: Software code that executes specified actions when programmed conditions are met.

Scenario planning: Development of multiple plausible futures to test strategic choices under uncertainty.

Signpost: An observable development indicating that a particular scenario may be emerging.

Platform dependence: Reliance on an external digital platform for distribution, data, revenue or audience access.

Algorithmic accountability: Responsibility for the effects, transparency and contestability of automated systems.

Media governance: Policies and structures for editorial, legal, ethical, data and organizational accountability.

Review Questions

Short Answer Questions

1. Distinguish invention from innovation in a media context.
2. What are the four tests for evaluating a media opportunity?
3. Why should an MVP preserve editorial accuracy and safety?
4. State two risks associated with platform dependence in the creator economy.
5. What is the purpose of a scenario signpost?

Long Answer Questions

1. Explain the design-thinking cycle and show how it could be applied to a new public-interest media service.
2. Discuss the benefits and limitations of lean experimentation for a legacy media organization.
3. Compare immersive media and decentralized technologies in terms of value, cost, governance and risk.
4. Explain how artificial intelligence may transform media work while preserving human accountability.
5. Describe the components of an integrated media venture plan.

Analytical / Application Questions

1. A proposed subscription newsletter attracts 8,000 qualified visitors and obtains 320 subscribers. Calculate its conversion rate and identify two additional measures needed before scaling the venture.
2. Design a four-week experiment for a creator-led audio service. State the target audience, hypothesis, MVP, success threshold, metrics and decision rule.
3. Construct two contrasting scenarios for a local news venture using platform concentration and audience willingness to pay as critical uncertainties. Recommend one robust strategic action and justify it.

Multiple Choice Questions with Answers

Question 1

Which statement best distinguishes innovation from invention in media?

A. Innovation is any idea that has not previously existed

B. Innovation occurs when a new idea is implemented and adopted to create value

C. Innovation refers only to the use of advanced digital technology

D. Innovation is the same as routine operational efficiency

Correct Answer: B. Innovation occurs when a new idea is implemented and adopted to create value

Question 2

Which activity best represents the empathize stage of design thinking?

A. Selecting a final pricing model

B. Writing a five-year financial forecast

C. Observing audience behavior and conducting contextual interviews

D. Launching a national advertising campaign

Correct Answer: C. Observing audience behavior and conducting contextual interviews

Question 3

A media MVP is best defined as:

A. A deliberately inaccurate version of a product

B. The smallest credible offering that generates meaningful learning

C. A fully developed product with every planned feature

D. A prototype tested only by internal staff

Correct Answer: B. The smallest credible offering that generates meaningful learning

Question 4

A service receives 240 subscriptions from 6,000 eligible visitors. What is its conversion rate?

A. 2%

B. 4%

C. 6%

D. 25%

Correct Answer: B. 4%

Question 5

A subscriber costs $18 to acquire and generates a monthly contribution margin of $6. What is the simplified payback period?

A. 2 months

B. 3 months

C. 6 months

D. 18 months

Correct Answer: B. 3 months

Question 6

Which is a major risk of creator dependence on a single platform?

A. Guaranteed revenue stability

B. Complete ownership of audience data

C. Exposure to algorithmic changes or account suspension

D. Elimination of reputational risk

Correct Answer: C. Exposure to algorithmic changes or account suspension

Question 7

What is the primary purpose of scenario planning?

A. To predict one certain future precisely

B. To create multiple plausible futures and test strategic robustness

C. To replace all market research

D. To guarantee the success of a business model

Correct Answer: B. To create multiple plausible futures and test strategic robustness

Question 8

Which question is most relevant when evaluating blockchain for a media application?

A. Is the technology fashionable among competitors?

B. Does the problem actually require a distributed ledger?

C. Can all editorial decisions be automated?

D. Will decentralization eliminate the need for governance?

Correct Answer: B. Does the problem actually require a distributed ledger?

Question 9

Which practice is most appropriate for responsible generative-AI use in journalism?

A. Publishing outputs without verification if they sound plausible

B. Concealing all use of synthetic content

C. Maintaining human review, source verification and disclosure policies

D. Entering confidential source information into any public AI system

Correct Answer: C. Maintaining human review, source verification and disclosure policies

Question 10

Civic Signals obtains 120 registrations from 2,000 qualified visitors. What is the registration rate?

A. 4%

B. 5%

C. 6%

D. 12%

Correct Answer: C. 6%