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Record W2795101335 · doi:10.1108/eemcs-06-2017-0127

Pacari Chocolate: preserving biodiversity, living without regret

2018· article· en· W2795101335 on OpenAlexaff
Nathaniel C. Lupton, Angélica Sánchez, Annette Kerpel

Bibliographic record

VenueEmerald Emerging Markets Case Studies · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategies and Innovation
Canadian institutionsUniversity of Lethbridge
FundersEuropean Commission
KeywordsRevenueMarketingEmerging marketsEntrepreneurshipBusinessProduct (mathematics)IndigenousTourismExcellenceLatin AmericansSustainabilityFinancePolitical science

Abstract

fetched live from OpenAlex

Subject area Emerging Markets. Study level/applicability Undergraduate, Masters. Case overview Pacari Chocolate is the flagship brand of SKS Farms CIA Ltda., located in Quito, Ecuador. The company specializes in organic chocolate production which it sells in Ecuador and exports to other Latin American, European and North American markets. The company began operation in 2002, founded by Carla Barbotó and her husband Santiago Peralta. Carla is the Director of SKS and Santiago is General Manager. The case is set just after Santiago negotiated a deal to supply Emirates Airlines with mini bars to be distributed to flight passengers. Santiago is excited about this new deal, which will provide a new revenue stream, enhance brand image and potentially create new customers. Carla and Santiago pursue excellence with their products, as evidenced by over 160 awards, many globally recognized. However, their mission is also very much social in that they seek to improve the lives of Andean farmers, indigenous peoples and broader Ecuadorean society. The principle author uses this case in a course on innovative approaches to engaging emerging market opportunities, in which shared (social + economic) value and the formation of strong national industries are key outcomes, to be addressed through complementary market and non-market entrepreneurship strategies. Expected learning outcomes Expected learning outcomes are as follows: to identify the contextual challenges faced by an emerging market firm, and explain what must be done to overcome them; to identify the role of a firm in developing a national competency in an agricultural product industry; to demonstrate the creation of “shared value” and examine how the social mission of a company can reinforce and sustain its economic value creating activities; and to generate and evaluate options for developing international markets when a firm has limited resources to invest in marketing activities. Supplementary materials Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes. Subject code CSS 3: Entrepreneurship.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0190.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.281
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2018
Admission routes1
Has abstractyes

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