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Record W4376639659 · doi:10.32920/22855490

Leveraging the balanced scorecard to reformulate the strategy of a performing arts theater: a stakeholders’ perspective

2023· preprint· en· W4376639659 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

Venuenot available
Typepreprint
Languageen
FieldComputer Science
TopicAdvanced Technologies in Various Fields
Canadian institutionsToronto Metropolitan UniversityLakehead University
Fundersnot available
KeywordsAttendanceBalanced scorecardBusiness administrationBusinessPolitical scienceMarketing

Abstract

fetched live from OpenAlex

<p>Purpose</p> <p>This study expands the performance management literature by developing a strategy map and balanced scorecard (BSC) for a large performing arts theater (PAT).</p> <p>Design/methodology/approach</p> <p>First, interviews with significant stakeholders identify key success factors (KSFs). Next, a survey is administered, and a structural model is employed to determine the importance of each KSF and their interdependent causal relationships within the PAT. Each KSF's controllability and room for improvement are also measured to facilitate implementation strategies.</p> <p>Findings</p> <p>The results reveal that the Financial Perspective plays a critical role in the PAT's success, while significant changes can be enacted by focusing on the Internal Processes Perspective. Regarding the individual KSF, the following emerge as the most critical: excellent reputation, attendance growth, increasing sponsorship and donation, and supporting the local arts community; however, PAT managers will have to be creative to enact change through these KSF as some are difficult to control or have little perceived room for improvement.</p> <p>Research limitations/implications</p> <p>The data were collected prior to, or at the beginning of the coronavirus disease 2019 (COVID-19) pandemic. Post-pandemic priorities for the organization may have changed.</p> <p>Practical implications</p> <p>By highlighting the relationships between different KSFs, this study provides PAT managers with a frame of reference for developing their BSC and performance metrics. It also offers PAT's managers a structured and adaptable approach for prioritizing their strategic choices and developing implementation plans for improved outcomes.</p> <p>Originality/value</p> <p>This study exemplifies the need for applied BSC studies in various sectors, including nonprofit organizations. Specifically, this study extends the performance management literature by providing an example of a large PAT's performance measures, the inter-relationships among KSF and the resulting strategy map. The results are significant because arts management is a unique discipline based upon a specific body of knowledge (Weinstein and Bukovinsky, 2009).</p>

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.893
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0050.007
Research integrity0.0000.002
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 head0.171
GPT teacher head0.327
Teacher spread0.156 · 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

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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