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IIM Indore

Strategic Management

arXiv preprint arXiv:2104.

An Algorithm to Effect Prompt Termination of Myopic Local Search on Kauffman-s NK Landscape

Extant research is vertically divided on the question whether exploration and exploitation constitute two ends of a continuum or whether they are orthogonal activities. We suggest that both characterizations are admissible, albeit under different sets of assumptions. Using March’s iconic model, we demonstrate that the continuum conception concerns leveraging an organization’s internal knowledge heterogeneity where managers use their prior knowledge and experiences to formulate actions to attain the maximum possible extent of organizational knowledge at equilibrium. In contrast, the orthogonal conception mainly concerns assimilating heterogeneous knowledge from sources outside the organization through risky experimentation, leading to order-creation in systems operating in far-from-equilibrium conditions. We further demonstrate that the change in outcome obtained by switching from low to high rate of exploitation is larger—and therefore easier to detect—for the continuum conception. We speculate that many managers and researchers favor conceptualizing exploration–exploitation in the continuum sense, for this reason. Moreover, companies obtain far higher organizational knowledge by functioning in the orthogonal mode, than what is attainable by functioning in the continuum mode. Organizations should, therefore, strive to create conditions that foster cultivation of outside knowledge through autonomous actions of employees. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.

World University root node

Computational and Mathematical Organization Theory

Back to the basics: reconciling the continuum and orthogonal conceptions of exploration and exploitation

Instances of Artificial Intelligence (AI) systems failing to deliver consistent, satisfactory performance are legion. We investigate why AI failures occur. We address only a narrow subset of the broader field of AI Safety. We focus on AI failures on account of flaws in conceptualization, design and deployment. Other AI Safety issues like trade-offs between privacy and security or convenience, bad actors hacking into AI systems to create mayhem or bad actors deploying AI for purposes harmful to humanity and are out of scope of our discussion. We find that AI systems fail on account of omission and commission errors in the design of the AI system, as well as upon failure to develop an appropriate interpretation of input information. Moreover, even when there is no significant flaw in the AI software, an AI system may fail because the hardware is incapable of robust performance across environments. Finally an AI system is quite likely to fail in situations where, in effect, it is called upon to deliver moral judgments—a capability AI does not possess. We observe certain trade-offs in measures to mitigate a subset of AI failures and provide some recommendations.

arXiv

AI failures: A review of underlying issues

Coeus

Why Do Strategic IT Change Projects Fail?

To validate prior agent-based models, public disclosure of model code is necessary, but not sufficient. Conceptual model replication, involving independent reproduction of a model without referring to the originator’s code, is crucial for detecting nonconformity between the publication text and the model implemented. We frame and evaluate four scenarios to expose the shortfalls of replication efforts that use the original study’s program code and neglect the published model description. We identify, evaluate, and offer recommendations regarding disparities between the text and the program code that generated the results reported in March’s classic study of exploration and exploitation in organizational learning. Based on our experience replicating his model, we suggest a two-step method of model verification—beginning with replicating the model from the published description, then turning to the program code of the original implemented model to account for divergent results. Exclusive reliance on either the published model description or the original program code does disservice to theory advancement, because disparities between the original conceptual and implemented models go unaddressed.

Fulltext

Strategic Organization

Replicating agent-based models: Revisiting March’s exploration–exploitation study

In real-world systems, phase transitions often materialize abruptly, making it difficult to design appropriate controls that help uncover underlying processes. Some agent-based computational models display transformations similar to phase transitions. For such cases, it is possible to elicit detailed underlying processes that can be subsequently tested for applicability in real-world systems. In a genetic algorithm, we investigate how a modest difference in the concentration of correct and incorrect knowledge leads to radically different outcomes obtained through learning efforts by a group of agents. We show that a difference in concentration of correct and incorrect knowledge triggers virtuous and vicious cycles that impact the emergent outcome. When virtuous cycles are in operation, delaying the onset of equilibrium attains superior outcomes. For the vicious cycles, reaching equilibrium quickly attains superior outcomes. Our approach helps uncover simple mechanisms by which Nature works, jettisoning the yoke of unrealistic assumptions endemic in mathematics-based approaches. Our explanatory model helps direct research to investigate concentrations of inputs that obtains outcomes on the favourable side of phase transitions. For example, by tracking change in concentration of relevant parameters, scientists may look for reasons why cells cease to reproduce fit cells in organs. This can help design rejuvenation of organs. Further, in the world of physics, our model may inform in situations where the dominant Ising model falls short.

ARXIV.ORG

A computational study explaining processes underlying phase transition

Purpose This paper aims to develop conceptual arguments questioning the efficacy of administration by the transaction cost economics (TCE) approach in an organization undergoing a major change.Design/methodology/approach The focus is on three distinct dimensions of organizational life where, as per prior research, TCE is likely to be inadequate: interdependence across transactions, high reliance on managerial foresight and inseparability of administrative decisions made at different points in time.Findings The climate of coercion and surveillance engendered by administration based on TCE approaches – that punishes deviation from goals, even when they are framed on inadequate knowledge – forestalls creative problem-solving that is necessary to address unforeseen developments that arise during change implementation. Fiat accomplishes within-group compliance in the change project sub-teams, but between-group interdependencies tend to be neglected, hampering organizational effectiveness. Moreover, attempts to create independent spheres of accountability for concurrent fiats regarding pre-existing and new commitments breed inefficiency and wastage.Research limitations/implications The malevolent aspects of TCE-based administration contribute to organizational dysfunctions like escalation of commitment and developing of silos in organizations.Practical implications To succeed in effecting a major organizational change, meaningful relaxation of demands for delivering on prior goals is required, along with forbearance of errors made during trial-and-error learning.Originality/value TCE-based administration is deleterious to an organization attempting a major change. Supremacy accorded to resolution of conflicts in distinct hierarchical relationships by the mechanism of fiat fails to address the needs of an organizational reality where multiple groups are engaged in a set of interdependent activities and where multiple, interdependent organizational imperatives need to be concurrently served.

Communication

International Journal of Organizational Analysis

Administration of an organization undergoing change: Some limitations of the transaction cost economics approach

In his seminal 1991 publication, March illustrates the continuum conception of exploration and exploitation by an organizational learning metaphor. Exploration involves allocating resources to experimentation. Exploitation involves doing known things better and focusing on execution. In March’s formal model, members of an organization deploy their collective human capital and engage in learning activities to fashion organizational knowledge. Collective human capital (CHC) is constituted by the aggregate beliefs of members, some of which are correctly aligned with respect to an objective external reality while others are neutral or misaligned. Organizational knowledge—constituting the validated knowledge in an organization—resides in the databases, rules, forms, norms, operating procedures and other artifacts in an organization. March’s computational experiments pertaining to the continuum conception suggest that more exploration is always preferable over more exploitation. We demonstrate that the reverse holds true when the CHC available in an organization is somewhat lower than that assumed in March’s experiments. Our research indicates that a section of extant research is mistaken in assuming that March’s formal model for the continuum conception suggests an inverted U-shaped relation between the extent of exploration and organizational outcome. Instead, the level of CHC determines whether it is rewarding to focus on exploration or exploitation. Thus, the formal model supports managerial intentionality towards exploratory and exploitative innovation through appropriate choice of the level of CHC. We call for a new “balance” discussion, focusing on the determinants of the minimum level of the non-preferred activity from among exploration and exploitation.

Management (France)

The continuum conception of exploration and exploitation: An update to March's theory

Emerging Multinationals (EMNEs) have attracted significant research attention in the recent years so are the internationalizing family firms (FFs) for being embedded in unique contexts - country for the former and family for the later. As FFs constitute a significant proportion of the EMNEs in some big emerging economies like India, drawing from both research streams, we investigate how family owned EMNEs differ from non-family EMNEs and how the heterogeneity of family owned EMNEs explains the full spectrum of internationalization of family owned EMNEs - spanning from lower commitment mode of exports to higher commitment mode of overseas foreign direct investments and subsidiary formations. Anchoring our research in the socioemtional wealth perspective in family business literature and behavioral risk taking theory we theorize how family owned EMNEs would differ in their internationalization trajectories from the non family owned EMNEs and how non-family professional managers shape the internationalization trajectories of family owned EMNEs differently as compared to those led by owner- managers. We test our predictions using a proprietary, longitudinal panel data set of 213 EMNEs from India featuring in the S&amp;P BSE 500 index covering a six year period from 2007-08 to 2012-13. We report general empirical support for most of our predictions.

Academy of Management Proceedings

Does Family Involvement Matter for Internationalization of Firms? An Investigation of Indian EMNCs

Replication of theory development by computational simulation modeling (TDCSM) is hardly a subject that is at the top of the mind of editors of premier journals. Notwithstanding the relative paucity of original work in this tradition (compared to empirical studies), we argue that replication of prior model work is important for good science. We set up the ontology of model work replication by distinguishing between various kinds of replication. We identify the Scientific Realist and Critical Realist streams as important consumers of TDCSM research. We demonstrate that both fields stand to lose if a culture of replication of computer models is missing. In the absence of focus on replication of model work, flawed modeling research persists in premier journals. Reviewers–functioning as gatekeepers–thwart publication of alternate ideas embodying findings different from their own. We build a case for providing space to conceptual replication, i.e. attempt to recreate a pioneer’s work based on description in the publication text. We suggest that a clear statement from journal editors–to publish research that unearths flaws in prior publications–is a fruitful way to clean the Augean stables, paving the way for scientific progress.

Ontology and Epistemology of Conceptual Replication of Computational Simulation Modeling Research

The difficulty in definitively linking outcomes of managerial action to organizational outcomes has been a festering issue in organizational research. The problem arises because it is not easy to separate the distinctive contributions of managers at intermediate stages, as well as the contribution of external factors beyond the control of managers. Specifically, certain managerial actions focusing on exploratory or exploitative innovation produce an intermediate output, organizational knowledge. From this base of organizational knowledge, further management actions craft the final output that eventually faces the market test. Drawing from complexity concepts, I argue that the probability of correctly fashioning the subset of key elements in the intermediate output may be a good measure of the probability of organizational success. I use March’s iconic computational simulation model to demonstrate the merits of this principle. I model the effect of complexity on managerial intentionality towards exploratory and exploitative innovation. I elicit important insights for research and practice by comparing organizational knowledge outcomes with the outcomes for probability of organizational success, in stable and moderately turbulent environment.

Inferring final organizational outcomes from intermediate outcomes of exploration and exploitation: the complexity link

We study a multinational corporation's (MNC) failure in implementing a firm-wide information technology system (ITS) project. To counter heightened competitive pressures, the MNC sought to improve its supply chain responsiveness by implementing the ITS project. However, since the headquarters (HQ) personnel lacked nuanced understanding of the micro issues in the subsidiaries, their design efforts turned out to be inadequate. Organizational practices that restrict member behavior to recipes from past knowledge served to amplify the problem—by disfavoring cooperation. Our study suggests a need to rethink the notion of the HQ as the design place. Further, there is a case for subsidiary personnel being afforded a greater say in design of changes to their work processes, given their higher exposure to process variety. This may offset the HQ-subsidiary power imbalance noted in prior literature. © 2015 Wiley Periodicals, Inc.

Thunderbird International Business Review

Learning from Project Failure: Globalization Lessons for an MNC

Computational simulation modeling is an important approach to formal theory development. It has all the advantages of mathematical models, and is additionally able to overcome problems related to discontinuities and disequilibrium conditions that mathematical models do not handle well. In social science research, a good deal of emphasis is placed on leveraging pioneering models, to further knowledge smoothly. However, two important philosophical paradigms, that of critical realism and scientific realism, sharply differ in terms of what is considered worth preserving and what is considered up for change, in work that follows that of the pioneer. Scientific Realists value knowledge accumulation. Models contradicting key assumptions of a pioneering model may not readily find favor with Scientific Realists. Critical Realists focus on generating new theory by the quickest possible means, particularly in areas where there is a paucity of theory. They favor leveraging the ontological aspects of pioneering models, while being open to contradicting its key assumptions. Thus, notwithstanding the surface sim- ilarity of both traditions promoting research by S. S. Chanda Indian Institute of Management Indore, Indore, India e-mail: sasanka2012@gmail.com S. Ray (&amp;) Indian Institute of Management Calcutta, Calcutta, India e-mail: sougata@iimcal.ac.in computational simulation modeling, knowledge advancement accomplished is of very different kinds, each with its own distinctive set of implications.

DECISION

Formal theory development by computational simulation modeling: a tale of two philosophical approaches

Extant research has provided ambiguous answers to the question as to what constitutes an ideal balance between exploration and exploitation, in stable and turbulent environments. Much of the literature emphasizes controlling organizational actions by means of predictions based on historical knowledge. In our study, we investigate organizational outcomes when such predictions are not possible and managers intentionally focus their firm on either exploratory or exploitative innovation. Using March’s iconic computational simulation model, we find that multiple exploration–exploitation combinations lead to equivalent, maximum organizational knowledge, establishing a rational basis for managerial intentionality toward exploratory or exploitative innovation. We further find that onset of environmental turbulence impacts an organization focusing on exploratory innovation in a way that is different from the way an organization focusing on exploitative innovation is impacted. The former is enabled to carry out an increasing level of its core activity, exploration. The latter is required to dial down its core activity, exploitation. Our findings suggest a resolution to conflicting prescriptions regarding appropriate response to onset of environmental turbulence endemic in the literature.

Optimal exploration and exploitation: the managerial intentionality perspective

Cognitive considerations arising from the functions of the Chief Executive Officer appear to have been ignored in strategy research. Taking a cue from Freeman’s stakeholder theory, I discuss the constituencies addressed by the CEO in performing his/her job function. I present a set of propositions based on extant research. I endeavor to commence a conversation that ultimately shapes the lines of inquiry regarding the contribution of managerial cognition to strategy.