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All Journal Indonesian Journal of Multidisciplinary Science Return : Study of Management, Economic and Bussines INJURITY: Journal of Interdisciplinary Studies Jurnal Ekonomi, Teknologi dan Bisnis
Raymond Rubianto Tjandrawinata
Universitas Katolik Indonesia Atma Jaya
Humanities Astronomy Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Public Health Social Sciences

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System Shift Risk, Publication Effects, and the Decay of Stock Return Predictability: An Exploratory Empirical Framework Raymond Rubianto Tjandrawinata
Return : Study of Management, Economic and Bussines Vol. 5 No. 6 (2026): Return: Study of Management, Economic and Business
Publisher : PT. Publikasiku Academic Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57096/return.v5i6.479

Abstract

The decay of stock return predictability after publication has been well documented, yet the underlying mechanisms are often explained as either statistical overfitting or market efficiency. This study introduces the System Shift Finance framework as a diagnostic lens to interpret why return predictability decays when a signal moves from private discovery into a public, crowded, and adaptive market environment. The framework codes seven system variables (System Condition, Domain Lock, Actor Complexity, Chokepoint Severity, Position Quality, Strategy Quality, and Feedback Maturity) and computes a System Shift Risk Score as the sum of pressure-side minus adaptive-side variables. Using three aggregate empirical phases drawn from the McLean and Pontiff-style return decay structure (in-sample discovery, out-of-sample pre-publication, and post-publication), this proof-of-concept validation employs descriptive statistics, correlation analysis, linear regression, logistic classification, feature importance, and cluster interpretation. Results indicate that a higher System Shift Risk Score is associated with higher total return decay, with Chokepoint Severity showing a particularly strong relationship with both total and post-publication decay. Position Quality and Strategy Quality behave as protective variables, while Feedback Maturity requires conceptual refinement as it appears to capture external market learning rather than internal adaptive capability. The study concludes that return predictability decay should be interpreted not only as a statistical or publication phenomenon but also as a system transition in which visibility, imitation, crowding, arbitrage pressure, and adaptive feedback jointly transform the profitability of trading strategies. The contribution lies in formalizing a systems-based explanatory architecture that can be scaled to anomaly-level datasets.
System Shift Risk, Human Capital, and Organizational Culture: A Proxy-Based Exploratory Validation with Methodological Safeguards Raymond Rubianto Tjandrawinata
Interdiciplinary Journal and Hummanity (INJURITY) Vol. 5 No. 6 (2026): Injurity: Interdiciplinary Journal and Humanity
Publisher : Pusat Publikasi Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58631/injurity.v5i6.1544

Abstract

This study examines whether the System Shift Framework can explain variation in organizational culture, human capital readiness, and resistance to adaptive change. Using a proxy-based firm-level dataset of 889 organizations, the analysis operationalizes seven System Shift dimensions: System Condition (SC), Domain Lock (DL), Actor Complexity (AC), Chokepoint Pressure (CP), Position Quality (POS), Strategy Quality (STR), and Feedback Maturity (FB). The composite risk index is calculated as SC + DL + AC + CP ? POS ? STR ? FB, where higher values indicate stronger cultural and systemic resistance to adaptive transformation. The analysis evaluates associations with Culture Effectiveness, Norms Alignment, Values-Norms Gap, Innovation Performance, Productivity Performance, Compliance and Ethics Performance, and System Shift Success. Results show that the System Shift Risk Score is strongly and negatively associated with Culture Effectiveness (r ? ?0.920), Norms Alignment (r ? ?0.979), and Compliance and Ethics Performance (r ? ?0.761). Regression models explain substantial variance in culture-proximal outcomes, particularly Norms Alignment and Compliance and Ethics Performance, while explanatory power is more modest for innovation and productivity outcomes. Classification analysis shows that logistic regression provides more stable discrimination than random forest under conditions of strong class imbalance, with approximately 2.6% of firms classified as System Shift Success cases. Random forest feature importance identifies Strategy Quality as the dominant predictor of System Shift Success, followed by chokepoint pressure, internal position, and system condition. Cluster analysis identifies three interpretable states: shift-ready and adaptive culture, transitional and mixed condition, and high-risk and resistant culture.
System Shift Risk, Chokepoint Severity, and Macroeconomic Resilience: Quarter-Level Exploratory Evidence from A Configuration-Based Framework Raymond Rubianto Tjandrawinata
Jurnal Ekonomi, Teknologi dan Bisnis Vol. 5 No. 6 (2026): Jurnal Ekonomi, Teknologi dan Bisnis
Publisher : Al-Makki Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57185/be88z728

Abstract

This study develops and evaluates the System Shift Economics framework as a configuration-based approach for diagnosing macroeconomic vulnerability and adaptive resilience. The framework proposes that forward-looking macroeconomic outcomes are shaped not only by current status categories, but by the interaction between structural pressure and adaptive capacity. Using 203 quarter-level macroeconomic observations — with forward-looking outcomes available for 199 observations — the study constructs a System Shift Risk Score from seven coded variables: System Condition, Domain Lock, Actor Complexity, Chokepoint Severity, Position Quality, Strategy Quality, and Feedback Maturity. The primary outcomes assessed are four-quarter-ahead GDP loss, crisis status, progression toward adaptive recovery, and overall success. The results provide exploratory support for the framework. Chokepoint Severity significantly predicts both four-quarter-ahead GDP loss and crisis probability. Strategy Quality and Feedback Maturity significantly predict Success and Progression in logistic models. The System Shift Risk Score outperforms the baseline status classification across all outcomes, improving explanatory power for GDP loss and discriminatory performance for crisis, success, and progression. Random Forest feature importance analysis identifies the composite risk score and Feedback Maturity as consistently relevant predictors. Cluster analysis further reveals three theoretically coherent regimes: Adaptive/low-risk, Transitional/medium-risk, and Stagnant/high-risk. The findings suggest that macroeconomic resilience is better understood as a system configuration rather than a static status condition. As the framework is newly operationalised, the evidence should be interpreted as exploratory rather than confirmatory; future validation will require independent samples, robustness checks, and external forecasting benchmarks.
System Shift Risk and The Measurement Architecture of Global Governance Indicators: Exploratory Evidence from WGI Source Metadata Raymond Rubianto Tjandrawinata
Indonesian Journal of Multidisciplinary Science Vol. 5 No. 9 (2026): Indonesian Journal of Multidisciplinary Science
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/ijoms.v5i9.1290

Abstract

Governance indicators are widely used in global policy and development to translate complex institutional conditions into comparable numerical metrics that guide decision-making, investment, and reform strategies. Despite their importance, composite indicators such as the Worldwide Governance Indicators (WGI) face persistent challenges related to measurement validity, source heterogeneity, and structural bias in data aggregation processes. This study investigates the measurement architecture of the WGI by analyzing 31 source units derived from metadata covering governance-related datasets. The WGI integrates multiple data sources, including surveys, expert assessments, and institutional records, to measure dimensions such as the rule of law, government effectiveness, and corruption control, covering more than 200 countries worldwide (World Bank, 2024). To address this gap, this study applies a System Shift framework that conceptualizes governance measurement as the interaction between structural pressure (SC, DL, AC, CP) and adaptive capacity (POS, STR, FB). The methodology includes correlation analysis, regression models, Random Forest, and cluster analysis to evaluate measurement risk, source quality, and representativeness. The findings show that chokepoint severity strongly increases measurement risk, while adaptive variables improve source quality and reliability. The System Shift Risk Score outperforms traditional source-type classification in predicting measurement outcomes. In conclusion, governance measurement quality is determined not only by indicator aggregation but also by the structural architecture of data sources.
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