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Record W2095286759 · doi:10.1108/11766091211216105

The use of performance measures: case studies from the microfinance sector in Kenya

2012· article· en· W2095286759 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueQualitative Research in Accounting & Management · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsYork University
Fundersnot available
KeywordsMicrofinanceSubsidyKenyaBusinessBureaucracySustainabilityPerformance measurementAccountingOrder (exchange)EconomicsActuarial sciencePublic economicsMarketingFinanceEconomic growth

Abstract

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Purpose The intent of microfinance institutes (MFIs) in developing countries is to provide loans to very poor people in order to help them transform their lives. MFIs tend to receive subsidies; sustainability is being sought to free MFIs from non‐market dependencies. Sustainability is expected to be achieved with “best practices,” of which management with performance measures is a component. The purpose of this paper is to examine the use of performance measures by three Kenyan MFIs, which are classified as formal and client based, and likely to use rational and explicit performance measures. Clients in these MFIs are placed into self‐help groups with two responsibilities: to provide mutual support and advice to the borrowing client; and to provide the MFI with a guarantee that loans of group members will be repaid. Design/methodology/approach Based on a review of the economics and performance measurement systems literatures, research questions were developed along with an interview guide. Case studies were used to administer an interview guide which was distributed to the respondents prior to the face‐to‐face interviews. Findings The study concludes that MFIs have relatively well‐developed performance measures that support their particular businesses. There was a good balance between the use of financial and non‐financial performance measures. However, output measures were more commonly used than process measures. The nature of the MFIs suggests the importance of performance measurement. The managers of the MFIs are concerned with performance measurement, as expected within a bureaucracy, and a top‐down demand is present. In addition, group members or clients are interested in performance measurement as each member guarantees the loans of all fellow group members who have loans with the MFI. Thus, the customers exert a bottom‐up demand for performance measurement. Originality/value The findings support the view that performance measures are a means for managing MFIs and are a likely requirement for sustainability. Furthermore, the findings have identified performance measures (similar to those at banks) that are appropriate for the three MFIs in Kenya. The findings are important since the identified performance measures may be adopted by other evolving MFIs in this relatively new sector. In addition, the findings contribute to a better understanding of the genesis of the less popular results and determinants performance measurement framework of Fitzgerald et al.

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.

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)0.016
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.481
GPT teacher head0.454
Teacher spread0.027 · 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