Notes on International Sourcing, Location Decisions, and Entry Modes

International Sourcing, Location Decisions, and Entry Modes

  • Overview: Companies face two key existential questions in international operations

    • What to manufacture (produce) domestically vs abroad

    • What to buy (source) from other producers (outsourcing) vs what to produce in-house (insourcing)

    • Illy as a running example: roasts coffee (core step) but sources packaging, machinery, logistics, and complementary products globally; sourcing is international for Italy as well as other elements.

    • The sourcing network of a country or company spans multiple actors and geographies, not just coffee beans.

  • Drivers and motivations (from a survey of >8,000 European firms):

    • Cost is the main driver of internationalization (cost advantages persist, but have evolved).

    • Over time, the cost differential between Western and Eastern countries has shrunk; transport costs are variable and can spike due to events (virus, war, Suez disruption, etc.).

    • Other drivers include proximity to culture, language, and suppliers; access to technology; market size; policy exposure; and risk diversification.

  • Key questions in configuring the international network: what to keep domestic vs foreign, where to locate, how to enter foreign markets, and how many steps of the supply chain to cover in each location.

  • Framework for location decisions: combination of hard data, soft factors, and managerial judgment

    • A framework uses multiple dimensions (cost, workforce, distance, infrastructure, business environment, economy and society, culture, etc.).

    • Data sources (illustrative):

    • Ease of Doing Business (World Bank) – measures ease of starting and operating a business; source for several sub-dimensions.

    • Logistics Performance Index (World Bank) – measures infrastructure quality, trade facilitation, logistics services, timeliness, tracking, etc.

    • Human Development Index (United Nations) – life expectancy, education, income, etc.

    • Additional national/international sources (ECE, ILO, Hofstede) for workforce, culture, and economic context.

  • Hofstede cultural dimensions and distance concepts:

    • Six Hofstede dimensions to gauge cultural distance between countries:

    • Power Distance, Individualism vs. Collectivism, Uncertainty Avoidance, Masculinity vs. Femininity, Long-term vs. Short-term Orientation, Indulgence vs. Restraints.

    • Purpose: to quantify cultural distance that might affect supplier-customer relationships, negotiations, and management practices.

    • Note: Cultural distance is a debated, imperfect measure; there is ongoing scholarly critique of its precision and applicability.

    • Practical use: compare a target country against a domestic reference to anticipate management challenges and collaboration dynamics.

  • Data-driven evaluation: a concrete, example exercise with three candidate locations (Hungary, Croatia, Czech Republic)

    • Case context: Long-standing Italian espresso machine maker (Long Leg) evaluating where to establish a manufacturing unit vs a commercial unit in Eastern Europe.

    • Data collected for each country on:

    • Ease of Doing Business (World Bank): sub-dimensions include starting a business (time, cost, min capital, procedures), dealing with construction permits, getting electricity, registering property, getting credit, protecting minority investors, paying taxes, trading across borders, enforcing contracts, resolving insolvency.

    • Logistics Performance Index (LPI): efficiency of customs, infrastructure quality, trade and transport, ease of arranging shipments, tracking, timeliness.

    • Human Development Index (HDI).

    • Export/Investment indices relevant to Europe (institutional sources; SACCE in the example).

    • Workforce availability and average hourly labor costs.

    • Cultural distance (Hofstede indices) and a calculated distance metric between Italy and each candidate country. Example distances (illustrative):

      • Italy to Croatia: ~12 hours by container shipment time (carrier-based estimate)

      • Italy to Hungary: ~22 hours

      • Italy to Czech Republic: ~26 hours

  • Example country rankings and data points used in the lecture (illustrative):

    • Ease of Doing Business – rank (where a lower rank is better in most rankings): Czech Republic ≈ 41, Croatia ≈ 51, Hungary ≈ 52 (labelled as best/worst within the set).

    • Logistics Performance Index (LPI) – country positions: Czech Republic ≈ 43, Croatia ≈ 43, Hungary ≈ 51.

    • Human Development Index (HDI): Czechia ≈ 32, Croatia ≈ 40, Hungary ≈ 46.

    • Cultural distance index (Hofstede-based): Hungary closest to Italy in the measured set, Croatia farthest among the three in the example.

    • Distances (logistic and geographic): Italy→Croatia ≈ 12 hours, Italy→Hungary ≈ 22 hours, Italy→Czech Republic ≈ 26 hours.

  • Turning data into a decision: multi-criteria decision analysis (MCDA)

    • The main idea: collect information on several dimensions and aggregate with weights to obtain a final score for each location.

    • Simple MCDA structure used in the lecture:

    • For production site: weights for each criterion (illustrative example):

      • Production site weight: wextproduction=0.20w_{ ext{production}} = 0.20

      • Workforce: wextworkforce=0.20w_{ ext{workforce}} = 0.20

      • Distance: wextdistance=0.50w_{ ext{distance}} = 0.50

      • Infrastructure: wextinfrastructure=0.50w_{ ext{infrastructure}} = 0.50

      • Business environment: wextbusiness=0.50w_{ ext{business}} = 0.50

      • Economy & society: wexteconextsoc=0.05w_{ ext{econ ext{-}soc}} = 0.05

      • Note: these weights are illustrative; in practice you would normalize weights to sum to 1 and adjust to reflect priorities.

    • For commercial unit (sales focus): a different set of weights (illustrative):

      • Example weights: w=[0.05,0.05,0.15,0.15,0.15,0.12,0.25]w = [0.05, 0.05, 0.15, 0.15, 0.15, 0.12, 0.25] for the seven criteria considered.

    • Scoring mechanism: convert each country’s rank on each criterion into a score (best = 3, next = 2, worst = 1) and compute a weighted sum:

      • ext{Score}i = igl(w1 igr) r{i1} + igl(w2 igr) r{i2} + \n dots + igl(wm igr) r{im} where r</em>ijoextrankscoreforcountryiextoncriterionjext(3=best,2=mid,1=worst).r</em>{ij} o ext{rank score for country } i ext{ on criterion } j ext{ (3=best, 2=mid, 1=worst)}.

    • In the example: the Czech Republic finished first in the production-focused MCDA and Hungary last, yielding Czech as the best location for a manufacturing unit; for a commercial unit, the ranking could shift depending on the weights, potentially placing Croatia ahead of Hungary in some scenarios.

    • The message: collect information from reputable sources, apply an MCDA with transparent weights, and then let data guide the decision while still allowing managerial judgment and experience to influence final choice.

  • Key interpretation and managerial takeaway:

    • The algorithm helps structure a decision by organizing data and revealing trade-offs across factors (costs, infrastructure, business climate, culture, and geography).

    • The final choice should reflect both calculated scores and managerial insight/instinct. The lecturer emphasized blending data with experience and intuition: “instincts are important, but must be informed by information.”

    • The approach can highlight country strengths/weaknesses to guide negotiation, risk assessment, and implementation planning.

  • Entry modes: a spectrum from least to most integrated and control

    • Distinguish between domestic production vs foreign production.

    • Indirect exports (low direct involvement):

    • Agent buyers (foreign buyers approach you indirectly)

    • Import/export companies and trading companies (specialize in moving goods internationally)

    • Consortia and networks (small firms pool resources to access foreign markets; e.g., a ham consortium)

    • Piggyback and franchising (two forms of trading agreements sharing distribution networks)

    • Direct exports (more control):

    • Independent sales agents, local distributors, and sales representatives (agents with signing authority on behalf of your company)

    • Representative offices (non-fiscal/legal entity; only representation)

    • Subsidiaries and branches (permanent establishments with tax and legal personality)

    • Outsourcing vs insourcing

    • Outsourcing = sourcing from third-party producers; insourcing = producing in-house or via wholly-owned facilities

    • Sourcing modes: imposed sourcing (supplier chosen by the client), intermediate sourcing (use an intermediary), direct sourcing (direct link to foreign producer)

    • Non-equity agreements: contract manufacturing, contract farming, and licensing; equity vs non-equity considerations

    • Equity-based entry modes (higher control, higher risk, higher capital):

    • Wholly owned foreign enterprises (WOFEs): full equity owned by the home company

    • Joint ventures (JV): new entity created with local partner sharing equity

    • Licensing and franchising (non-equity but IP-based control):

    • Licensing: licensor grants usage rights to IP/brand/know-how

    • Franchising: franchisor grants a business model/brand to a franchisee for royalties

    • Contract farming and sourcing examples (coffee industry):

    • Contract farming: a buyer (transnational company) contracts with farmers/cooperatives for supply; risk and revenue shared; includes technical assistance, quality control, and guaranteed marketing of coffee; common in coffee supply chains (e.g., Illy, Nestle scenarios)

    • Contract manufacturing: contract-based production with a foreign producer while maintaining control over IP and branding

    • Notable real-world patterns:

    • Starbucks: multiple modes across markets (joint ventures, wholly owned, licensing, exclusive distribution, and alliances) with diverse country-specific arrangements (e.g., 80% ownership in Australia; minority JV in Austria; licensing in China; wholly owned in the UK)

    • Nestlé: sourcing through buying centers in some countries; relies on intermediaries in others; emphasizes supply reliability rather than owning plantations

    • Illy: coordinates supply chain quality with direct grower relationships; does not own plantations; focuses on coordination, not vertical integration

  • Decision-tree for entry modes (a simplified view):

    • Step 1: Domestic production or foreign production?

    • Step 2: If foreign, outsource or insource?

    • Step 3: If insource, go it alone or form a joint venture?

    • Step 4: If going alone, pursue Greenfield investment or acquire an existing unit?

    • Step 5: Consider non-equity alliances (sourcing agreements, licensing) vs equity arrangements (JV, WOFEs)

  • Practical advice and philosophy for international expansion

    • Gather data from reputable sources for a sound baseline; supplement with field due diligence, local market knowledge, and expert guidance.

    • Use MCDA to structure decisions, but preserve a space for intuition and experiential learning.

    • Be mindful of country-specific peculiarities (e.g., Chaebol in Korea vs Keiretsu in Japan) and how these power structures influence markets and supply chains.

    • Recognize that data sources have strengths and limitations; use multiple indices to cross-check and triangulate.

    • Cultural distance matters but is not determinative; it interacts with other factors (legal, economic, infrastructure, and operational risks).

  • Ethical, philosophical, and practical implications

    • Sourcing from farmers and small producers (e.g., contract farming) can reduce risk for buyers but may shift risk to farmers; ensure fair terms, transparency, and capacity-building.

    • Global supply chains are exposed to political, environmental, and social risks; diversifying supply and maintaining contingency plans is prudent.

    • Intellectual property and brand protection become central in licensing, franchising, and strategic alliances; choose partners with strong governance.

    • Economic polarization and power concentration (e.g., Keiretsu/Chaebol-like systems) may influence market dynamics; consider antitrust, competition, and local regulatory environments when forming alliances.

    • Ethical sourcing raises questions about labor practices, environmental sustainability, and community impact; integrate ESG considerations into the decision framework.

  • Key formulas and equations (summary):

    • MCDA score (production-focused example):
      extScore<em>i=w</em>extproductionr<em>i1+w</em>extworkforcer<em>i2+w</em>extdistancer<em>i3+w</em>extinfrastructurer<em>i4+w</em>extbusinessr<em>i5+w</em>exteconextsocr<em>i6ext{Score}<em>i = w</em>{ ext{production}} r<em>{i1} + w</em>{ ext{workforce}} r<em>{i2} + w</em>{ ext{distance}} r<em>{i3} + w</em>{ ext{infrastructure}} r<em>{i4} + w</em>{ ext{business}} r<em>{i5} + w</em>{ ext{econ ext{-}soc}} r<em>{i6} where each r</em>ijo3,2,extor1r</em>{ij} o 3, 2, ext{ or } 1 depending on the country’s rank on criterion j, and the weights sum to 1 (after normalization).

    • General MCDA aggregation (seven criteria example for commercial unit):
      extScore<em>i=(w</em>1r<em>i1)+(w</em>2r<em>i2)+(w</em>3r<em>i3)+(w</em>4r<em>i4)+(w</em>5r<em>i5)+(w</em>6r<em>i6)+(w</em>7r<em>i7)ext{Score}<em>i = \bigl(w</em>1 r<em>{i1}\bigr) + \bigl(w</em>2 r<em>{i2}\bigr) + \bigl(w</em>3 r<em>{i3}\bigr) + \bigl(w</em>4 r<em>{i4}\bigr) + \bigl(w</em>5 r<em>{i5}\bigr) + \bigl(w</em>6 r<em>{i6}\bigr) + \bigl(w</em>7 r<em>{i7}\bigr) with the weights w</em>jw</em>j as chosen by the analyst (illustrative set provided above).

    • Distances (logistics Times example):
      t{ ext{Italy} ightarrow ext{Croatia}} = 12 ext{ h}, \n t{ ext{Italy}
      ightarrow ext{Hungary}} = 22 ext{ h},
      t_{ ext{Italy}
      ightarrow ext{Czech}} = 26 ext{ h}.

  • Final takeaways from the instructor’s closing message

    • Knowledge is the first investment: collect information about the foreign markets, their nature, and their context before committing capital.

    • Combine data with experience and instinct to guide strategic choices; data informs but does not replace strategic judgment.

    • The Greek case studies will be discussed next time; prepare by reading about entry modes and related questions (why, what, where, how).

  • Recurring questions and discussion prompts (from the session)

    • How would you weigh different factors if your goal were production-centric vs sales-centric?

    • How might Chaebol/Keiretsu-like systems influence supplier networks in Korea or Japan compared to Western markets?

    • How would you design an MCDA if you wanted to include ESG criteria (environmental, social, governance) alongside economic factors?

    • How can contract farming and licensing agreements be structured to balance risk and reward for both buyers and producers?

  • Real-world references mentioned in the talk

    • World Bank: Ease of Doing Business; Logistics Performance Index

    • United Nations Development Programme (HDI)

    • Hofstede Institute (cultural dimensions)

    • Industry examples: Illy, Nestlé, Starbucks, Tata Coffee (India), Illy-JAB licensing, Nestlé buying centers in the Philippines, contract farming in coffee supply chains, and Sun Tzu’s Art of War as a guiding metaphor for knowledge and strategic planning

  • Next steps suggested by the instructor

    • Open and work with the Excel file for the Exercise (country comparisons)

    • Practice collecting country data, applying MCDA weights, and interpreting results

    • Prepare to discuss the Greek case studies in the next session

  • Note on scope and context

    • The session emphasizes a practical, data-informed approach to international expansion, with attention to both quantitative indices and qualitative factors (culture, politics, geography, and strategic partnerships).

  • Quick recap of the core ideas

    • Two core questions: what to produce vs buy; where to locate and how to enter.

    • Use reputable data sources to quantify costs, infrastructure, and business environment.

    • Apply an MCDA with clearly stated weights to compare locations for different objectives (manufacturing vs commercial).

    • Understand entry modes ranging from exporting and intermediaries to wholly owned subsidiaries, joint ventures, licensing, and contract farming.

    • Always blend data with judgment, experience, and a risk-aware mindset.

  • Final reminder from the instructor

    • If you want to succeed abroad, know the market and know yourself; knowledge reduces risk and increases triumph potential. "Know yourself and know the situation".