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Record W3037751193 · doi:10.1108/jkm-01-2020-0075

The influence of investors’ opinions of human capital and multitasking on firm performance: a knowledge management perspective

2020· article· en· W3037751193 on OpenAlexaff
Shashank Vaid, Benson Honig

Bibliographic record

VenueJournal of Knowledge Management · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHuman multitaskingBusinessContext (archaeology)Human capitalMarketingIndustrial organizationPerspective (graphical)Knowledge managementEconomicsPsychologyMarket economy

Abstract

fetched live from OpenAlex

Purpose The purpose of this study is to examine the disruption-adaptation associated with knowledge management (KM) of entrepreneurial multitasking of top strategy and tactics executive (TSTE) succession in positions responsible for both S and T. This provides insight into KM and firm performance during turbulent periods. Design/methodology/approach The study examines investor’s opinions of human capital in the context of managerial succession. The data was based on 900 publicly available appointment announcements between 2006–2014, allowing for the examination of 459 observations of succession in 51 industries. Findings The findings indicate that the relationship between KM of entrepreneurial multitasking and firm performance was more positive for high innovation firms than for low innovation firms. As well, the relationship between investors’ opinions of a top executive manager’s human capital and firm performance is more positive for small firms than for large firms and more positive for high innovation firms than for low innovation firms. Research limitations/implications The study contributes to the literature by systematically examining the announced appointment of executives in one context where KM of entrepreneurial multitasking is prevalent – across marketing strategy and sales tactics (hereafter, S and T) responsibilities – for multiple firms listed at major US stock exchanges across a wide range of industries, using lagged performance data to discern performance outcomes. It highlights important issues related to organizational structure and human capital for firm performance and KM in dynamic environments. Further research could examine the impact on firm performance of a change in structure – from a joint sales and tactics position to a sales or tactics position and vice versa. By studying the impact of change to and from an intertwined position, future scholars can determine the level of risk stemming from coordination uncertainty changes with time. Practical implications Of practical relevance, the study shows that vesting dual responsibility for S and T in one executive during managerial succession may not be as universally valuable or adaptive as previously thought. One practical extension of this research may also be that larger firms that are more likely to have clearly defined silos may find that such vesting of multitasking responsibility not as valuable. High innovation and small firms may gain from new executives’ multitasking responsibility for S and T. Thus, firms should think twice before vesting S and T responsibilities with one incoming executive during the leadership change. Social implications Responsibility for both S and T compounds ambiguous accountability, frequently leaving the locus of customer-related problems unclear, and therefore unsolved. Originality/value Extant research has overlooked the relationship between the top management team’s (TMT) abilities to multitask firm performance over time across contexts of external and internal change, operationalized as firm innovation and firm size. Nor have studies explored the firm performance implications of external stakeholders’ opinions of such human capital across these contexts. A novel measure of executive-specific human capital – abnormal returns generated the appointment announcement, is introduced. Understanding the capability of a top executive to simultaneously multitask both S and T responsibilities is a critical component of KM; also relevant are investors’ opinions of their human capital, a particular oversight given the challenge of the “great transformational leader” with servant leadership theory (Carayannis et al., 2017; Gregory Stone et al., 2004).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.253
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2020
Admission routes1
Has abstractyes

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