Never have a crisis like COVID-19

Current circumstances caused by COVID-19 pandemic pose a unique challenge to businesses. How could businesses survive? What strategic options do businesses have when they effectively engage such a challenge? Delving into the inquiry, we explore and investigate different strategic approaches to measure their effectiveness. For the study’s explorative and investigative purposes, our investigation involves a set of tests at both business and corporate levels. Using 224 responses from the leaders and key individuals of Korean startups, we tested the effectiveness of strategic options using the notion of ambidexterity and alliances, and mergers and acquisitions. Using the ambidexterity lens, we found exploitation and exploration indirectly affect firm performances and are still effective under COVID-19. We also found “reinforcing the relationship with existing alliances,” a corporate-level approach, to be effective.

Victorious and Hierarchical: Past Performance as a Determinant of Team Hierarchical Differentiation

Hierarchies emerge as collectives attempt to organize themselves toward successful performance. Consequently, research has focused on how team hierarchies affect performance. We extend existing models of the hierarchy-performance relationship by adopting an alternative: Performance is not only an output of hierarchy but also a critical input, as teams’ hierarchical differentiation may vary based on whether they are succeeding. Integrating research on exploitation and exploration with work on group attributions, we argue that teams engage in exploitation by committing to what they attribute as the cause of their performance success. Specifically, collectives tend to attribute their success to individuals who wielded greater influence within the team; these individuals are consequently granted relatively higher levels of influence, leading to a higher degree of hierarchy. We additionally suggest that the tendency to attribute, and therefore grant more influence, to members believed to be the cause of success is stronger for teams previously higher (versus lower) in hierarchy, as a higher degree of hierarchical differentiation provides clarity as to which members had a greater impact on the team outcome. We test our hypotheses experimentally with teams engaging in an online judgement task and observationally with teams from the National Basketball Association. Our work makes two primary contributions: (a) altering existing hierarchy-performance models by highlighting performance as both an input and output to hierarchy and (b) extending research on the dynamics of hierarchy beyond individual rank changes toward examining what factors increase or decrease hierarchical differentiation of the team as a whole.

Effects of Personality Traits and Team Context on Individual Innovative Behavior (Exploitation and Exploration)

This study analyzed how personality traits, team context, and the interaction between the two affect individual exploitation and exploration. Analyses of data from two Korean firms revealed that personality traits have an effect on individual exploitation and exploration activities. Specifically, the authors found that those with high-level openness to experiences engaged in high-level exploration activities. By contrast, those with high-level conscientiousness pursued high-level exploitation activities. For individual exploitation and exploration activities, the team context perceived by individuals was also important. Furthermore, this study confirmed the effect of the interaction between personality traits and team context on individual exploitation and exploration activities.

A Modified Slime Mould Algorithm for Global Optimization

Slime mould algorithm (SMA) is a population-based metaheuristic algorithm inspired by the phenomenon of slime mould oscillation. The SMA is competitive compared to other algorithms but still suffers from the disadvantages of unbalanced exploitation and exploration and is easy to fall into local optima. To address these shortcomings, an improved variant of SMA named MSMA is proposed in this paper. Firstly, a chaotic opposition-based learning strategy is used to enhance population diversity. Secondly, two adaptive parameter control strategies are proposed to balance exploitation and exploration. Finally, a spiral search strategy is used to help SMA get rid of local optimum. The superiority of MSMA is verified in 13 multidimensional test functions and 10 fixed-dimensional test functions. In addition, two engineering optimization problems are used to verify the potential of MSMA to solve real-world optimization problems. The simulation results show that the proposed MSMA outperforms other comparative algorithms in terms of convergence accuracy, convergence speed, and stability.

Ambidextrous Utilisation of Artificial Intelligence in Policing: A Conceptual Framework

This conceptual paper contributes to the literature by showing the need to understand artificialintelligence (AI) in policing outside the task-dependent environment of today. We examine AI in policing by outlining its potential opportunities and challenges in exploration for today’s policing tasks and beyond. Based on these findings, we reflect upon Holmqvist’s prior theorisation of the dynamics of organizational ambidexterity (i.e., exploitation and exploration). The paper offers future research avenues for public administration and general management researchers interested in AI.

Social Entrepreneurship Education: A Combination of Knowledge Exploitation and Exploration Processes

It is widely accepted that entrepreneurship education has become a key development priority for coping with uncertainty and for addressing various social, economic, and technological concerns related to health, living conditions, education systems, employment, and economic growth. In recent times we have witnessed a proliferation of Entrepreneurship Education (EE) programs and initiatives with the aim to promote the creation of new skills, competencies, and capabilities to deal with a wide range of social issues and for creating new societal. The COVID-19 pandemic situation has introduced radical challenges to the society and has impacted significantly, especially the process of entrepreneurial competencies, skills and attitudes development. This paper aims to provide insights into knowledge mechanisms and learning strategies that have been activated for the effective creation of entrepreneurship competencies. We have based our evaluation on an exploratory analysis of 10 program studies that deliver social entrepreneurship education. The paper presents elements of originality under two perspectives: it proposes a framework with the main patterns characterizing social entrepreneurship education (SEE), and it argues that the creation of an entrepreneurship mindset and competencies is an evolutionary process that combines dynamic knowledge exploitation and exploration mechanisms.

Exploitation–Exploration Model of Media Multitasking

Media multitasking has been long considered as a distraction, as something that is inherently negative or irrational. Yet, casual observations and study findings indicate that in the current permanently online, permanently connected society, people still media multitask frequently, sometimes in spite of their knowledge of the costs. In this article, we introduce the exploitation–exploration model of media multitasking (EEMMM), which proposes that media multitasking occurs as a natural part of the waxing and waning of our task engagement: When primary task engagement (exploitation) begins to wane, alternative tasks become more attractive (exploration). In the first part of this paper, we delineate the limitations of the current perspective of media multitasking as a distraction. The second part provides an exposition for our model: What defines behavior exploitation and exploration, and why maintaining an optimal trade-off between the two is important; the everyday, media-related cues for exploiting and exploring; and the neurobiological evidence of a brain system that supports the transition from exploitation to exploration. Lastly, we show how our approach may explain why people media multitask spontaneously and in spite of their knowledge of the costs, and why not all media multitaskers are able to multitask optimally. We conclude the paper with an agenda for future media multitasking research based on the proposed framework.