Knowledge Integration, Synthesis, and Engineering (KnISE)

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KnISE is a new community of
synthesizers, builders, and solvers!


KnISE /naɪs/- sounds "nice"!

The Knowledge Integration, Synthesis, and Engineering (KnISE) community is formed in response to the growing fragmentation of knowledge in business research. KnISE seeks to become a catalyst for knowledge accumulation and integration on a timely basis and at a massive scale into ready-to-use decision solutions. We will integrate science (open science, meta-theory, and meta-methods) and technology (information systems and collective intelligence platforms) into actionable solutions for broad societal impact.


   
 

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Founders:
Victor Zitian Chen (the University of North Carolina at Charlotte; GoPeaks) - zchen23@uncc.edu
Kai Larsen (University of Colorado Boulder) -kai.larsen@colorado.edu
Sebastian Boell (University of Sydney) -sebastian.boell@sydney.edu.au
Brian Fisher (Simon Fraser University, UBC) - bfisher@sfu.ca
Roland Müller (Berlin School of Economics and Law) -roland.mueller@hwr-berlin.de
Carina Antonia Hallin (IT-University of Copenhagen; MIT Center for Collective Intelligence) -caah@itu.dk
Frank Bosco (Virginia Commonwealth University; metaBUS) -fabosco@vcu.edu
Jamie Field (West Virginia University) -james.field2@mail.wvu.edu
Patricio Duran (Saint Louis University) -patricio.duran@slu.edu
Benjamin Mueller (HEC Lausanne) -benjamin.mueller@unil.ch


BACKGROUND

The business and management knowledge has been rewarding incremental research that develops and tests coherent hypotheses of interest from a simplified view of complex problems. This reductionist approach is reinforced by discipline boundaries, peer pressures for granular specialization, technical constraints of periodical outlets (limited space, scope, and frequency), and lack of diversity in scholarly incentives (publication counts and citations). Consequently, both researchers and practitioners in management face a knowledge fragmentation conundrum. The literature, data, and communities are increasingly fragmented, distributed into silos, and disconnected. It has become exceedingly difficult to develop complete explanatory frameworks to connect all the knowledge silos because the effects across these silos are poorly understood. There is an increasing number of experts on piecewise topics but limited solutions to complex social challenges.

WHY NOW?

Today, our knowledge is at a volume that makes integration possible and at a degree of fragmentation that makes integration necessary. Time is ripe to (re)invent a science-practice ecosystem with mutually supportive components that give rise to timely and massive knowledge accumulation. We advocate developing an open community engaged in globally coordinated efforts whose collective goal is to integrate theories, models, constructs, and their relationships into a unified knowledge system. The new IG will engage existing and new AOM members to construct the critical elements of a unified knowledge system.

Based on an open discussion at an All-Academy Theme Symposium, such elements include (1) establishing models and standards for integrative meta-frameworks as a critical knowledge product; (2) developing new technologies to assist human researchers for knowledge synthesis; (3) exploring new methods for sharing and consolidating knowledge; (4) hosting a new digital library (e.g., Github-like platform) to democratize the access to knowledge synthesis; and (5) incentivizing members and the broad community in a new polymathic “Yes and” mindset (e.g., hosting knowledge synthesis competitions).

WHO WILL BE MEMBERS OF THIS COMMUNITY?

KnISE will consist of four groups of members: (1) integrated researchers in business and management; (2) knowledge synthesis technology developers; (3) knowledge access solution developers; and (4) practitioners seeking synthesized and ready-to-use solutions. We expect a large proportion of members being practitioners looking for ready-to-use, synthesized solutions.

#ResearchMethods #ManagementConsulting #ManagementEducationandDevelopment #Knowledge #meta-analysis #Research