A Proposal and Call for Funding for GoPeaks.org


Global OpenLabs for Performance-Enhancement Analytics and Knowledge System



“Without a common framework to organize findings, isolated knowledge does not cumulate.”

…2009 Nobel Laureate Elinor Ostrom


Mission, Motivation, and Significance


After more than six decades of scientific research of business administration, the stock of our knowledge is at a volume that makes knowledge synthesis for business applications possible, and meanwhile the structure of this knowledge has reached a degree of fragmentation that makes knowledge creation activities more confused without a shared knowledge navigation system. Like the pharmaceutical industry which historically emerged as a new ecosystem to synthesize scientific research into medical interventions as well as to guide and fund basic research, time is ripe to (re)invent a science-practice ecosystem in business administration to synthesize disperse scientific findings into business analytics 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” reflects the underlying philosophy that humans are driven to reach their peak of multiple goals and values. The first letter “G” is reserved for the namesake of the primary funder.


Consisting of many globally coordinated labs in both the academia and the industry, GoPeaks’ goal is to consolidate disperse theoretical and empirical efforts from all academic sources (journals, books, working papers, teaching cases, patents, etc.) into a unified digital library that organizes and updates all variables and models to comprehensively predict business performance at multiple levels and from multiple stakeholder perspectives. It is also an Amazon-style exchange platform for knowledge creators (researchers) and knowledge users (decision makers, analytics professionals) to communicate and share resources (e.g., model for data; data for model; merging data into data platforms; integrating models into meta-frameworks, etc). Essentially, this initiative is an interface between consolidated knowledge (e.g., meta-frameworks) from academia and consolidated resources (e.g., merged big data platforms from multiple sources, etc.) from the industry.


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 and software engineering, whereas a key component at the decision maker’s level is missing. Prior to data and IT is the articulation of the business problem, and translation of it into a comprehensive analytic framework on what data to collect, whom to ask/survey, how to accurately measure variables, how to organize these variables into a predictive/process model, and what the existing empirical efforts (mostly in academic sources) say about the hypotheses. While analytics professionals do consult decision makers to develop their databases and models, the current practice is relatively disconnected from our knowledge development in management and social sciences. This new research initiative will take on this task by constantly organizing and presenting existing scientific findings as a common pool for business decision makers to draw ideas and build (or to verify their own) comprehensive frameworks given any business problems.


Second, from a knowledge perspective, it enables the accumulation of old knowledge and guides the discovery/creation of new knowledge. Most scientific research in business administration tends to be based on discipline- or specialty-specific silos (due to the themes of academic trainings and outlets) and partial testing (due to difficulties in accessing full big data and replications). Without integrating these partial efforts together, it is difficult to timely translate scientific research into reliable analytic frameworks as mentioned above. While systematic reviews and meta-analysis are feasible techniques that can integrate scientific publications into a relatively unbiased and comprehensive model, the current incentive systems of the business school/university and academic funding agencies typically motivate scientific researchers to focus on fundamental/ground-breaking projects, discouraging knowledge integration. With its own funding sources and incentives, this new research initiative will help to fill this gap. To organize existing knowledge and suggest knowledge gaps, this initiative also forms a shared knowledge navigation system to guide new knowledge discovery and creation activities. Prior to the publication of knowledge creation/discovery, it provides an independent reference for both authors and journals to judge whether a new manuscript is built on the solid foundation, novel in its contribution, and important in its target of the knowledge gaps. After the publication, through constant (re)testing using big data, meta-analysis, and relative weight analysis (of predictors and competing theories) in a performance-predicting meta-framework, the new system enables a new incentive system to rate researchers, journals, and editors based on replicability and relative weight in predicting key performance measures, which are not captured by the current business school/university system based on publication counts, citations, and impact factors.


While this initiative is still at the concept level, over the years I have been conducting several studies to build up the intellectual foundation and built a network of prominent scholars and industry partners to enable this initiative. Many of them can be founding advisors and partners at the “GoPeaks”. Below are a few examples:


Efforts to form a community and policy framework


1. With Michael Hagstroem (then COO at McKinsey Analytics), Jennifer Roberts (then Charlotte Mayor), and Mirsad Hadzikadic (Director of Data Science Initiative, UNC Charlotte), I hosted a Charlotte City Club “Big Thinkers” Forum in 2017 on how to form an industry-university-government community to promote resource exchanges on analytics. I presented a proposed knowledge navigation system (Figure 1 above) integrating science and practice. The event was attended by 90+ educational, business, and public-sector leaders in the Charlotte region.


2. With Dr. Denise Rousseau (University Professor at Carnegie Mellon University; 2005 President of Academy of Management) and Dr. Michael Hitt (University Professor Emeritus at Texas A&M University; 1997 President of Academy of Management), I am proposing a new research society of business professors and doctoral students to contribute review articles and meta-analyses to the “GoPeaks” library. We did a 2017 Academy of Management Panel Symposium on “Time is ripe for knowledge synthesis: (Re)inventing technologies, outlets, and incentives” with three other former Academy presidents, Dr. Jim Walsh (University of Michigan; 2010 President), Dr. Susan Jackson (Rutgers University; 2011 President), and Dr. Duane Ireland (Texas A&M University; 2014 President). The panel discussed ideas to encourage knowledge integration as a new agenda for management studies and how it can complement the existing scientific journal-centric system. In the panel, I presented a concept demo for a GoPeaks ecosystem (YouTube link to the right). Dr. Hitt, Dr. Rousseau, and I are organizing an academic committee for “GoPeaks” and have drafted a vision paper (under review a journal) on the key elements of the “GoPeaks” ecosystem.


3. I organized and chaired the 2016 Academy of Management Professional Development Workshop (PDW) on “Creating a more reliable and cumulative knowledge ecosystem: Meeting senior editors of five leading journals”, with Arun Rai (Editor-in-Chief, MIS Quarterly), Kris Byron (Associate Editor, Academy of Management Review), Christopher Marquis (Associate Editor, Administrative Science Quarterly), Gilad Chen (Editor, Journal of Applied Psychology), and John Cantwell (then Editor-in-Chief, Journal of International Business Studies). The panel discussed how to redesign journal presentations and editorial policies so that knowledge is more accessible and accumulative.


4. With Dr. Henry Mintzberg (McGill University), Dr. Peter Lorange (former President of IMD and Lorange Institute, former board member of AACSB and EFMD), Dr. William Glick (then Chair of AACSB, then Dean of Jones Graduate School of Business, Rice University), and Dr. JC Spender (former Dean of NYIT, Co-editor of Oxford Handbook of Management Education), I hosted the 2015 Academy of Management Panel Symposium on “Designing the future business schools”. The panel discussed ideas to reform the incentive systems of business schools towards a better integration between science and practice.


Efforts to build up the intellectual foundation


5. With Dr. Michael Hitt (Texas A&M University), I have finished a critical review of the current knowledge ecosystem of management research and education. It is currently under Revise and Resubmit at a journal.


6. With Dr. George Banks (University of North Carolina at Charlotte), Yuanyuan Li (PhD student at Rutgers University), and Dr. Erik Gonzalez-Mulé (Indiana University), I am co-authoring a meta-analysis of about 40 empirical studies on post-foreign entry performance. For science, we lay out a general template for synthesizing alternative theories and mapping the most generous set of predictors into a unified meta-framework on post-entry performance, as well as context boundaries. For practice, our findings can help to identify knowledge gaps (e.g., lack of replications) and inconsistencies (e.g., conflicting conclusions in replications), as well as to build a science-informed training model for foreign investment analytics.


7. With Dr. Michael Hitt (Texas A&M University), Dr. Marc van Essen (University of South Carolina), and Dr. Steve Sauerwald (University of Illinois at Chicago), I am co-authoring a meta-analysis of 150+ primary studies on country-level predictors for sustainable corporate performance matrix, that is, under what institutional conditions companies are more likely to achieve positive correlations among performance measures from different stakeholder perspectives (e.g., shareholders, customers, employees, societies). It is to build up a comprehensive matrix of multi-stakeholder performance measurement under the philosophy of “total value creation”– that is, “Peaks”. For science, the findings can help business researchers from all disciplines (stakeholder domains) to relate their research to performance indicators from other disciplines (or domains), and to find common drivers of multiple stakeholder performance indicators. For practice, we help analytics professionals to introduce and monitor a holistic set of corporate performance indicators, as well as to build a science-informed training model for “total value creation” (“Peaks”) analytics.


8. I am proposing a knowledge mining software to assist researchers to locate and organize scientific findings from digital libraries into analytic frameworks. One goal is to create a semi-automatic tool to identify inconsistencies and redundancies in the literature in terms of definitions, conceptualizations, theories and logics, as well as measures.


Scalability and extensions over the long term


9. From a business science-practice ecosystem to a general social science-practice ecosystem: Professional subjects such as education, public administration, public policy, development, and law may all fit into a generalized social science-practice ecosystem. As shown in Figure 2 above, in the proposed knowledge navigation system map, we can replace “Business Literature” in Figure 1 with “Subject Area Literature” of a professional school that has reached the volume ready for knowledge synthesis. Similarly, the “peaks” business performance can be replaced with a social performance matrix relevant to any of these professional subjects. As an example, a research topic for a social science-practice synthesis could be a general predictive model to explain the long-term balance between wealth and equality of a society.


10. From a prescriptive (i.e., performance-enhancement) teleology to a descriptive scientific teleology: Knowledge fragmentation is not a problem unique for professional schools, but for academia in general. As shown in Figure 3 above, we can replace “Business Literature” in Figure 1 with the literature of any academic disciplines (e.g., economics, psychology, sociology, political science, etc.) or interdisciplinary areas (e.g., organization science, sustainability) that faces the same problem of high volume and high fragmentation of knowledge, which requires knowledge synthesis to solve grand challenges and complex problems. We also need to replace the “peaks” business performance measure to a consolidated matrix of dependent variables (e.g., human behavior, environmental sustainability) relevant in these disciplines/areas. As an example, a research topic for a science synthesis could be the general predictive model for human behavior – a grand challenge puzzling all social scientists.


11. From information democracy to knowledge democracy: The ultimate goal of GoPeaks (and its various extensions) is to connect all knowledge together in a unified web through daily electronic devices (computers, smartphones), on which any consolidated knowledge will be updated timely and drive synchronized updates in all connected areas, in both practice and science. It is a step to create and evolve a collective “brain and neurological system” connecting all humans and organizations together, independent of any private or political interests. One challenge facing our societies today is democracy of information without democracy of reason, rationality, and knowledge, leading to fake/biased news and misguided populism. Scientific knowledge (or a tool to utilize it) now is not accessible to all. By connecting all knowledge together and making it accessible to all, GoPeaks aims to neutralize biased opinions and counter misguided populism.


Boundary conditions and limitations


No medicine is panacea; neither is GoPeaks. There are two things GoPeaks can do, and one thing it cannot. First, it can synthesize theories and empirical evidence to find reliable thinking short-cuts to automate some decision rules, as well as to identify their context boundaries. Second, it can de-automate some rigid thinking short-cuts that are not supported by empirical evidence or are only applicable in a very narrow and hardly replicable context. Third, it cannot completely replace human judgement. Business (and any other professional subjects) is not a science. It is a practice that integrates sciences, arts, philosophy, and many other disciplines to enhance performance. Very often big business decisions are made without a general theory or sufficient evidence, which require non-routine based innovative and design thinking (as well as entrepreneurial doing) (see my Vlog SHIVA devoted to these skills). Having said that, GoPeaks can help to reduce uncertainties in decisions, saving resources for more non-routine-based work.


I am looking to present some of the working projects to potential funders and industry partners to materialize this proposal into a research lab (the first lab and the coordination office of GoPeaks).


Victor Zitian Chen, PhD

Assistant Professor of International Management

Belk College of Business

University of North Carolina at Charlotte


Founding Coordinator


Personal Web: www.ChenZitian.com

Tel: 1 (980) 800-1123

Email: founder@GoPeaks.org


2017-2027 © Victor Zitian Chen