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Record W4200496983 · doi:10.1108/jfbm-11-2021-0136

Family business successors' motivation and innovation capabilities: the case of Kosovo

2021· article· en· W4200496983 on OpenAlexaff
Asdren Toska, Veland Ramadani, Léo‐Paul Dana, Gadaf Rexhepi, Jusuf Zeqiri

Bibliographic record

VenueJournal of Family Business Management · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMindsetOriginalityFamily businessValue (mathematics)MarketingQualitative researchBusinessQualitative propertyPublic relationsEmerging marketsManagementSociologyPolitical scienceEconomicsSocial scienceComputer science

Abstract

fetched live from OpenAlex

Purpose This study aims to investigate the second-generation successors’ motives to join family businesses and their ability to generate innovation within them. Design/methodology/approach A qualitative methodology is used in this study. Data were collected through structured interview with the second-generation representatives, where the data obtained helped us to come to the results and answer the research questions of the study. A total of 15 interviews were conducted. Findings The findings of this study show that the second generation is motivated to continue the family business, cases show that successors since childhood have been oriented towards building an entrepreneurial mindset and also after entering the family business have generated innovation. Originality/value The study will bring theoretical implications to the family business literature, providing scientific evidence for the second generation of family businesses, from an emerging country such as Kosovo. As Kosovo is an emerging country, the study will contribute to the literature, suggesting other studies by emerging countries in this way to see the similarities and differences.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.730
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.007
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.247
Teacher spread0.217 · 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 teacher head, not a consensus.

Study designObservational
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

Citations33
Published2021
Admission routes1
Has abstractyes

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