GoPeaks.org | Mission
After more than six decades of scientific research of business administration, the stock of our knowledge is at a volume ready for knowledge accumulation and synthesis for evidence-based prescriptions. Yet, this knowledge is increasingly fragmented, making knowledge accumulation exceedingly difficult. There is an increasing pressure for specialization without enough incentives for “big picture” organizing of knowledge. Without a navigation system that guides knowledge accumulation at a broad scale, knowledge creation is becoming increasingly difficult, inefficient, and confused.
Like the pharmaceutical industry which historically emerged as a new ecosystem to synthesize scientific research into medical interventions as well as to guide the funding for basic research, time is ripe to (re)invent a science-practice ecosystem in business administration to integrate disparate scientific findings into analytics and decision tools and to more systematically guide and fund academic research.
I thus propose a new industry-academia research partnership named “Global OpenLabs for Performance-Enhancement Analytics and Knowledge System” (or “GoPeaks” for short). The plural term “Peaks” represents the underlying philosophy that a healthy business society is pluralistic, driven to satisfy multiple goals, values, and stakeholder concerns.
Distinct from any formal organizations, GoPeaks initiative seeks to build a unique open-innovation community. Consisting of many globally coordinated labs in both the academia and the industry, GoPeaks’ goal is to consolidate disperse theoretical and empirical efforts from multiple knowledge sources (journals, books, working papers, teaching cases, patents, archival data, emergent data in the daily life and workplace contexts, etc.). The consolidated knowledge will be hosted at an integrative digital library, which constantly organizes and updates variables, their causal mechanisms, and models into meta-frameworks. Such meta-frameworks serve as a tool to holistically analyze and predict business performance concerning all stakeholders.
It also seeks to build an Amazon-style exchange platform, where data and knowledge resources can be exchanged and integrated among its creators (researchers; data providers) and consumers (decision makers, analytics professionals). Examples include model for data, data for model, data mergers onto platforms, and model/theory integrations into meta-frameworks, etc.
Essentially, this initiative creates an open-innovation intersection between consolidated knowledge (e.g., meta-frameworks) from the research community and consolidated resources (e.g., data platforms) from the industry.
Significance and Impact
The value of this new research partnership is twofold.
First, from a business perspective, the existing practice of analytics lies in the advancement of data science (“what”) and software engineering (“how”), whereas the reasoning and logics of decision making (“why”) are relatively uninvolved. Big decisions are made on big reasons, rather than only big data or models. Prior to data and software is the understanding of a complex business problem, and articulation of it into a comprehensive analytic framework by considering multiple logics, perspectives, theories, and data sources.
While analytics professionals do consult decision makers to develop their databases and models, the current practice in this interaction is relatively disconnected from the rising stock of knowledge in management- and social sciences.
GoPeaks will thus take on this task by organizing and presenting existing research findings as a common knowledge pool. There, business decision makers (and their supporting teams) can draw ideas and evidence for developing their reasoning frameworks ready for data analytics.
Second, from a knowledge perspective, it enables the accumulation of old knowledge and guides the discovery/creation of new knowledge. “Without a common framework to organize findings, isolated knowledge does not accumulate”, said 2009 Nobel Laureate Elinor Ostrom. Much of the scientific research (in business administration and academia in general) is conducted in silos, limited by training specialty, outlet focus, and elite journal incentives that emphasize coherence and novelty. This research is also often published based upon incomplete evidence and potential risks of sample overfitting, due to difficulties in accessing representative, large-scale data and lack of incentives for replications. Without integrating these fragmented efforts together, it is difficult to timely bridge knowledge silos into comprehensive and accumulative analytic frameworks ready for analytics.
GoPeaks seeks to (re)invent the incentives in its community to fill this gap. By organizing and synthesizing existing knowledge, mapping the complete knowledge frontiers, identifying knowledge gaps, and making this information highly accessible, this initiative seeks to form a shared knowledge navigation system to guide new knowledge creation activities.
The incentives of GoPeaks will cover research activities seamlessly before and after publications.
Prior to the publication, GoPeaks provides an independent and thorough “fair hearing” for knowledge creators and outlet editors to judge the contribution of a research idea. It also seeks to build an open digital outlet inviting original submissions under rigorous, accumulative, and machine-friendly practices, including triple-blinded review (editors/reviewers/contributors all blinded from each other) and machine-assisted judgment of contributions. Since GoPeaks seeks to become a reliable knowledge source where actual decisions and practices will directly draw prescriptions, all publications will need to pass through an independent auditing group, which will be responsible for data auditing and privacy protection policies. To partially incentivize these practices, GoPeaks also seeks financial contributions from diverse sources to provide generous funding for professional auditing, editing, and reviews.
After the publication, through constant (re)testing using large-scale data analytics, meta-analysis of such analytics from multiple sources, and relative weight analysis (of predictors and competing theories), the new system will rate researchers and their works on replicability and relative weight in predicting key performance measures. These post-publication incentives will complement the existing academic rating system, which focuses almost exclusively on publication counts, citations, and impact factors.
Overall, GoPeaks helps to convince more funding sources to support accumulative research (and its fragmented supporting research silos), by making connections explicit among different knowledge silos and explain how they can make enduring social impacts (after integration).
2017-2027 © Victor Zitian Chen