1 Introduction
2 Theoretical background
2.1 Core elements of organizational resilience
2.2 Overconfidence as a personality trait
3 Method and selection procedure
Date | Database | Results |
---|---|---|
10/15/2021 | ABI/Inform Complete | 481 |
10/17/2021 | Business Source Premier and EconLit via EBSCO | 547 |
Total
| 1.028 | |
Duplicates
| 352 | |
Total number of literature sources
|
676
|
Keyword | Number of hits |
---|---|
CEO overconfidence | 100* |
Manager overconfidence | 42 |
Overconfident CEO | 17 |
Overconfident CEOs | 67 |
Overconfident manager | 2 |
CEO hubris | 59 |
CEOs hubris | 8 |
Manager hubris | 1 |
Managers hubris | 3 |
4 Results
4.1 Description of the sample
Author(s) (year) | Managerial overconfidence and material resources | Managerial overconfidence and social resources | Managerial overconfidence and procedural resources | Decision making processes | CSR | Moderators | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Mergers and acquisitions
|
Investment behavior and share buybacks
|
Financing preferences/dividend payments
|
Tax policy
|
Reactions of investors, analysts and lenders
|
Financial performance
|
Accounting
|
Auditing
|
Innovation processes
| |||||
Adam et al. (2015) | X | ||||||||||||
Adam et al. (2020) | X | ||||||||||||
Aghazadeh et al. (2018) | X | ||||||||||||
Ahmad et al. (2021) | X | ||||||||||||
Ahmed and Duellman (2013)
| X | X | |||||||||||
Aktas et al. (2019) | X | ||||||||||||
Aliani et al. (2016) | X | ||||||||||||
Almeida et al. (2021) | X | ||||||||||||
Alqatamin et al. (2017) | X | ||||||||||||
Andreou et al. (2018) | X | ||||||||||||
Andreou et al. (2019) | X | ||||||||||||
Andriosopoulos et al. (2013) | X | ||||||||||||
Andriosopoulos et al. (2020) | X | ||||||||||||
Arena et al. (2018) | X | X | |||||||||||
Ataullah et al. (2018) | X | ||||||||||||
Banerjee et al. (2015) | X | ||||||||||||
Banerjee et al. (2018) | X | X | |||||||||||
Beavers and Mobbs (2020)
| X | ||||||||||||
Bouwman et al. (2014) | X | ||||||||||||
Bouzouitina et al. (2021) | X | X | |||||||||||
Brown and Sarma (2007)
| X | X | |||||||||||
Bukalska (2020)
| X | X | |||||||||||
Campbell et al. (2011) | X | ||||||||||||
Chai et al. (2016) | X | ||||||||||||
Chen and Lu (2015)
| X | ||||||||||||
Chen et al. (2014) | X | ||||||||||||
Chen et al. (2015) | X | X | |||||||||||
Chen et al. (2020) | X | ||||||||||||
Choi et al. (2018) | X | ||||||||||||
Chu et al. (2019) | X | ||||||||||||
Chung and Hribar (2021)
| X | X | |||||||||||
Chyz et al. (2019) | X | ||||||||||||
Cormier et al. (2016) | X | X | |||||||||||
Croci et al. (2010) | X | ||||||||||||
Deshmukh et al. (2013) | X | ||||||||||||
Dick et al. (2021) | X | ||||||||||||
Doukas and Petmezas (2007)
| X | ||||||||||||
Duellman et al. (2015) | X | ||||||||||||
Eichholtz and Yönder (2015)
| X | X | |||||||||||
Engelen et al. (2015) | X | X | |||||||||||
Ferris et al. (2013) | X | ||||||||||||
Galasso and Simcoe (2011)
| X | X | |||||||||||
Gul et al. (2020) | X | ||||||||||||
Guo and Ding (2020) | X | ||||||||||||
Gupta et al. (1997) | X | ||||||||||||
Hayward and Hambrick (1997)
| X | X | X | ||||||||||
Hirshleifer et al. (2012) | X | X | X | ||||||||||
Ho et al. (2016) | X | ||||||||||||
Hsieh et al. (2014) | X | X | |||||||||||
Hsieh et al. (2018) | X | ||||||||||||
Hsu et al. (2017) | X | X | |||||||||||
Hsu et al. (2021) | X | ||||||||||||
Huang et al. (2011) | X | ||||||||||||
Huang et al. (2016) | X | ||||||||||||
Huang-Meier et al. (2016) | X | X | |||||||||||
Hur et al. (2019) | X | ||||||||||||
Iyer et al. (2017) | X | ||||||||||||
Ji and Lee (2015)
| X | X | |||||||||||
Kaplan et al. (2012) | X | ||||||||||||
Kim (2013)
| X | X | |||||||||||
Kim and Kim (2019)
| X | X | |||||||||||
Kim et al. (2016) | X | X | |||||||||||
Kim et al. (2018) | X | X | |||||||||||
Kim et al. (2021) | X | ||||||||||||
Kolasinski and Li (2013)
| X | X | |||||||||||
Koo and Yang (2018)
| X | ||||||||||||
Kouaib and Jarboui (2016)
| X | ||||||||||||
Kubick and Lockhart (2017)
| X | ||||||||||||
Lai et al. (2017) | X | X | |||||||||||
Lai et al. (2021) | X | ||||||||||||
Lee (2016)
| X | ||||||||||||
Lee (2021)
| X | ||||||||||||
Leng et al. (2021) | X | ||||||||||||
Li and Sullivan (2020)
| X | X | |||||||||||
Li and Tang (2010)
| X | X | |||||||||||
Lin et al. (2005) | X | ||||||||||||
Lin et al. (2008) | X | ||||||||||||
Lin et al. (2019) | X | X | |||||||||||
Lin et al. (2020) | X | ||||||||||||
Liu and Lei (2021)
| X | ||||||||||||
Liu and Nguyen (2020)
| X | ||||||||||||
Loureiro et al. (2020) | X | ||||||||||||
Lu et al. (2015) | X | ||||||||||||
Malmendier and Tate (2005)
| X | ||||||||||||
Malmendier and Tate (2008)
| X | X | |||||||||||
Malmendier et al. (2011) | X | ||||||||||||
McManus (2018)
| X | ||||||||||||
Mitra et al. (2019) | X | X | |||||||||||
Mueller and Brettel (2012)
| X | ||||||||||||
Park and Chung (2017)
| X | X | |||||||||||
Park and Kim (2009)
| X | ||||||||||||
Park et al. (2018) | X | X | |||||||||||
Pavićvić and Keil (2021) | X | ||||||||||||
Phua et al. (2018) | X | ||||||||||||
Pierk (2021)
| X | ||||||||||||
Reyes et al. (2020) | X | ||||||||||||
Rovenpor (1993)
| X | ||||||||||||
Sauerwald and Su (2019)
| X | X | |||||||||||
Schrand and Zechman (2012)
| X | ||||||||||||
Schumacher et al. (2020) | X | ||||||||||||
Seo and Sharma (2018)
| X | ||||||||||||
Seo et al. (2017) | X | ||||||||||||
Simon and Houghton (2003)
| X | ||||||||||||
Tan (2017)
| X | ||||||||||||
Tang et al. (2015a) | X | X | |||||||||||
Tang et al. (2015b) | X | X | |||||||||||
Tang et al. (2018) | X | ||||||||||||
Tebourbi et al. (2020) | X | ||||||||||||
Ting et al. (2016) | X | X | |||||||||||
Vivian and Xu (2018)
| X | ||||||||||||
Wang et al. (2016) | X | ||||||||||||
Wang et al. (2018) | X | ||||||||||||
Wong and Wang (2018)
| X | X | |||||||||||
Yang (2015)
| X | ||||||||||||
Zavertiaeva et al. (2018) | X | ||||||||||||
Zhang et al. (2020) | X |
Author(s) (year) | Focus of investigation | Sample | Measurement of managerial overconfidence |
---|---|---|---|
Adam et al. (2015) | Relation between managerial overconfidence and risk management using derivative financial instruments of companies | Period: 1989–1999, sample: 92 gold mining companies from North America | Managerial overconfidence is expressed by means of the self-attribution bias, i.e. managers increasingly apply speculative hedging strategies using derivative financial instruments, recognizable by a higher hedge ratio, provided that they have been able to achieve successes (positive cash-flows) in the past |
Adam et al. (2020) | Relation between managerial overconfidence and the use of performance pricing provisions in loan contracts (performance-sensitive debt) | Period: 1992–2010, sample: 1,199 unique CEOs | Option-based |
Aghazadeh et al. (2018) | Relation between managerial overconfidence and the cost of equity | Period: 1996–2012, sample: 13,535 firm-year observations | Three option-based measured variables are combined into one variable by means of factor analysis |
Ahmad et al. (2021) | Impact of managerial overconfidence on entrepreneurial strategic decision making | Sample: 169 questionnaires of entrepreneurs operating in the manufacturing sector (SMEs), located within the twin cities Rawalpindi-Islamabad in Pakistan, with employment size up to 250 employees | |
Ahmed and Duellman (2013) | Relation between managerial overconfidence and conservative accounting | Period: 1993–2009, sample: companies of the S&P 1500 Index, 14,641 firm-year observations | Four measures: an option-based measure, a net buyer measure similar to Malmendier and Tate (2005), and two measures that capture overinvestment due to overconfidence |
Aliani et al. (2016) | Consequences of managerial overconfidence for the tax policy of Tunisian companies | Period: 2002–2011, sample: 28 companies listed on the Tunisian stock exchange | Measurement by questionnaire |
Aktas et al. (2019) | Relation between managerial overconfidence and the value that the stock market attributes to cash | Period: 1993–2013, sample: exclusion of financial and utility companies, 12,105 firm-year observations | Option-based and for robustness testing also media-based as well as use of gender |
Almeida et al. (2021) | Moderating effect of managerial overconfidence on the relation between a sudden cash inflow and innovativeness | Period: 2002–2003, 2005–2006, 2000–2007 (depending on the analysis), sample: 37 firms in the control group and 317 firms in the treatment group | Option-based |
Alqatamin et al. (2017) | Relation between managerial overconfidence and the level of forward-looking information disclosure | Period: 2008–2013, sample: 1,206 firm-year observations of Jordanian firms listed on the ASE | Three measures. (1) option-based, (2) investment decisions according to Campbell et al. (2011) and Ahmed and Duellman (2013), 3) leverage ratio |
Andreou et al. (2018) | Relation between managerial overconfidence and reactions to announcements of share buybacks | Period: 1992–2009, sample: U.S. companies, 16,025 buyback announcements | Three measures: (1) media-based, (2) option-based, (3) gender-based |
Andreou et al. (2019) | Relation between managerial overconfidence and diversification | Period: 1993–2010, sample: 1,360 companies and 8,262 firm-year observations for stock-based measurement of overconfidence, 1,860 companies and 10,843 firm-year observations for media-based measurement of overconfidence | Two measures: (1) measure based on purchases of shares of the own company, (2) media-based |
Andriosopoulos et al. (2013) | Influence of managerial overconfidence on the buyback of shares | Period: 1997–2006, sample: 400 share buyback announcements by companies mainly listed in the UK, 13,378 buyback transactions | Option-based |
Andriosopoulos et al. (2020) | Influence of managerial overconfidence on overpayment | Period: 82,425 firm-year observations comprised of 11,504 unique U.S. industrial firms, sample: 1975–2011 | Option-based |
Arena et al. (2018) | Importance of CEO hybris for environmentally friendly innovations | Period: 2010–2012, sample: 338 firm-year observations, 134 companies | A measure was generated by factor analysis from the following three measures: (1) media-based, (2) relative compensation, (3) photo |
Ataullah et al. (2018) | Relation between managerial overconfidence and the maturity of debt instruments | Period: 2000–2010, sample: 865 firm-year observations, 192 British listed companies | Two measures: (1) based on computer-assisted voice and sound analyses of management board statements, (2) based on the acquisition ratio of company shares |
Banerjee et al. (2015) | Influence of an independent board on managerial overconfidence, investigated using the transition under the Sarbanes-Oxley Act and changes in the NYSE/NASDAQ listing rules (SOX) | Period: 1992–2012, about 22,000 firm-year observations | Option-based, for robustness testing also media-based, measurement based on options in relation to income and other measures |
Banerjee et al. (2018) | Relation between managerial overconfidence and shareholder class actions | Period: 1996–2012, sample: depending on the model, between 174 and 194 observations from a sample of over 22,000 firm-year observations with 1,375 claims | Option-based, to test the robustness of the results measurement by means of media-based and share-based measures according to Kolasinski & Li (2013) |
Beaver and Mobb (2020) | Relation between managerial overconfidence and the CEOs’ activities related to the work at board | Period: 1996–2011, sample: 114,052 independent director-year observations for 20,527 firm-years | |
Bouwman et al. (2014) | Relation between CEO optimism and earnings management | Three option-based measures | |
Bouzouitina et al. (2021) | Relation between managerial overconfidence and corporate social responsibility | Period: 2010–2017, sample: 2,360 UK firms listed on the FTSE 400 Index | Two measures: (1) Media-based, (2) net share purchase ratio following Malmendier and Tate (2005) |
Brown and Sarma (2007) | Relation between managerial overconfidence and acquisition activity | Period: 1994–2003, sample: 65 companies from the S&P/ASX 50 Index | Media-based |
Bukalska (2020) | Relation between managerial overconfidence and investment-cash flow sensitivity as well as financial constraints | Period: 2010–2016, sample: 145 surveys from non-listed enterprises based in Poland with non-overconfident managers (78 companies and 546 firm-year observations) and overconfident managers (67 companies and 469 firm-year observations) | Survey based on Wrońska-Bukalska (2016) |
Campbell et al. (2011) | Relation between CEO optimism and CEO dismissal | Period: 1992–2005, sample: 12,334 CEO-firm year observations, 3,352 CEO-firm combinations, 294 forced changes | Three measures: (1) option-based, (2) based on the purchase of company shares according to Malmendier and Tate (2005), (3) based on the investment level |
Chai et al. (2016) | Influence of managerial overconfidence on company takeovers, taking into account the deviation from the target capital structure | Period: 1993–2011, sample: exclusion of financial and utility companies, 1,432 announced and implemented company takeovers | Option-based |
Chen and Lu (2015) | Relation between managerial overconfidence and share buyback costs | Period: 2001–2013, sample: exclusion of financial companies, companies listed in Taiwan that carried out open market repurchases (ORMs) in the period mentioned, 2,749 ORMs | Four measures according to Schrand and Zechman (2012): (1) industry-adjusted investment level, (2) measurement based on acquisition activity, (3) measurement based on debt-to-equity ratio, (4) measurement based on the issue of convertible bonds and preference shares |
Chen et al. (2014) | Impact of R&D investments as a result of managerial overconfidence on business performance | Period: 1980–1994, sample: 477 listed U.S. companies | Option-based |
Chen et al. (2015) | Effect of managerial overconfidence on dealing with wrong decisions | Period: 1994–2008, sample: 576 forecasts from 217 CEOs of U.S. listed companies who are making profit forecasts for the first time in their profession | Three different measures: (1) media-based, (2) option-based, (3) successes achieved in the past analogous to Hayward & Hambrick (1997) |
Chen et al. (2020) | Effect of managerial overconfidence on firms’ cash holdings | Period: 1992–2016, sample: 17,942 firm-year observations of 1967 U.S. firms | Option-based |
Choi et al. (2018) | Relation between managerial overconfidence and investment cash flow sensitivity | Period: 1992–2012, sample: exclusion of financial and utility companies, 15,446 firm-year observations of companies in the S&P 1500 | Two option-based measures |
Chu et al. (2019) | Impact of managerial overconfidence on earnings management | Period: 1985–2010, sample: 392 AAER firm-year observations, 43,939 non-AAER firm-year observations | Option-based |
Chung and Hribar (2021) | Impact of managerial overconfidence on likelihood and timeliness of goodwill impairments | Period: 2003–2012, sample: varies depending on variables, total number of firm-quarter observations equals 23,295 | Two option-based measures and one measure based on forecasts following Hribar and Yang (2016) among others. It should be noted that the last measure can measure both a personality trait and a cognitive bias. |
Chyz et al. (2019) | Relation between managerial overconfidence and tax avoidance | Period: 1990–2007, sample: the sample of companies with a change of CEO between 1990 and 2007 is based on Fee et al. (2013), 1,090-1,220 firm-year observations (depending on the tax avoidance variable used) | Option-based and eight additional measures to test the robustness |
Cormier et al. (2016) | Relation between CEO hubris and misinformation | Period: 1995–2009, sample: 16 Canadian companies whose CEOs are accused of misconduct or who disclose such conduct and are subject to formal allegations by regulators that resulted in a financial or administrative penalty | Three dimensions are considered: (1) “relation with the world”: (the prerequisite for the emergence of CEO hubris is power, in that CEOs or their families hold more than 5% of the shares or the CEO founded the company), (2) “relations with the self”: certain corporate structures and business models, (3) “relations with others”: CEO awards, press reports and buy recommendations from stock analysts |
Croci et al. (2010) | Relation between managerial overconfidence and the success of company takeovers in phases of high and low market valuation | Period: 1990–2005, sample: buyers are British companies, 848 takeovers | Option-based |
Deshmukh et al. (2013) | Relation between managerial overconfidence and dividend payments | Two measures: (1) option-based, (2) media-based | |
Dick et al. (2021) | Relation between managerial overconfidence and CSR engagement in family firms versus other firms | Period: 2014, sample: 343 Polish companies (mainly medium-sized and nearly all non-listed) | Measures capturing the positive deviation between managers’ subjective evaluation of the firms’ situation and the firms’ objective economic condition. It should be noted that these measures partly can measure both a personality trait and a cognitive bias. |
Doukas and Petmezas (2007) | Relation between self-attribution bias, managerial overconfidence and returns on private acquisitions | Period: 1980–2005, sample: exclusion of financial and utility companies, 5,334 successfully completed acquisitions (all private companies) of British listed companies | Overconfidence is determined by the increased takeover activity of managers over a period of three years, overconfidence on the part of managers exists if up to five or more company takeovers have taken place within this period |
Duellman et al. (2015) | Relation between managerial overconfidence and audit fees | Period: 2000–2010, sample: exclusion of financial and insurance companies, 7,661 firm years | |
Eichholtz and Yönder (2015) | Impact of managerial overconfidence on the investment activity of U.S. real estate investment companies | Period: 2003–2010, sample: 146 U.S. real estate investment companies | A net buyer measure similar to Malmendier and Tate (2005) is applied to the purchase and sale of real estate, CEOs are judged to be overconfident if they buy more real estate than they sell over the entire sample period |
Engelen et al. (2015) | Relation between managerial overconfidence and entrepreneurial orientation in companies | Period: 2005–2007, sample: 142 observations for 61 companies | Option-based according to Campbell et al. (2011) |
Ferris et al. (2013) | Relation between managerial overconfidence and company takeovers | Period: 2000–2006, sample: exclusion of financial and state-owned enterprises, companies from the global ranking of Fortune magazine, global sample of U.S., Japanese, English, French and German companies | Media-based |
Galasso and Simcoe (2011) | Impact of managerial overconfidence on innovation policy | Period: 1980–1994, sample: exclusion of financial, insurance and real estate companies, 290 companies, 627 managing directors, 3,648 firm-year observations | Option-based |
Gul et al. (2020) | Impact of managerial overconfidence on the relation between CSR engagement and empire building | Period: 1996–2015, sample: 16,635 firm-year observations of U.S. firms | Option-based |
Guo and Ding (2020) | Moderating effect of managerial overconfidence on the relation between performance discrepancy and a firm’s patent application rhythm | Period: financial data: 2011-2015, sample: 6,814 firm-year observations of 1,730 listed companies | Measurement based on prediction errors in managers’ earnings forecasts. It should be noted that this measure can measure both a personality trait and a cognitive bias. |
Gupta et al. (1997) | Effect of changed conditions (in the wake of the Financial Institutions Reform, Recovery, and Enforcement Act (FIRREA) of 1989) on acquisition activity driven by Hybris | Period: 1979–1992, sample: 138 merger offers (78 pre-act, 60 post-act) from buyers of solvent savings banks whose offers were approved by the Federal Home Loan Bank Board (FHLBB) or the Office of Thrift Supervision (OTS) in the period 1979–1992 | Hubris is defined according to Roll (1986) and measured as follows: Hubris should result in a non-positive correlation between the gains of the target firm and of the buyer, at least for the sub-sample with positive total wealth gains. |
Hayward and Hambrick (1997) | Influence of managerial hubris on premiums paid for company takeovers and the moderating effect of the board structure on this | Period: 1989–1992, sample: pairs of publicly traded companies involved in a takeover between 1989 and 1992 with payments in excess of $100 million, 106 acquisitions | Three measures: (1) company performance, (2) media praise for the CEO, (3) self-importance measured by relative compensation |
Hirshleifer et al. (2012) | Relation between managerial overconfidence and pioneering and innovative behavior | Period: 1993–2003, sample: exclusion of financial institutions and utilities, 2,477 CEOs, 9,807 firm-year observations | Two measures: (1) option-based, (2) media-based |
Ho et al. (2016) | Impact of managerial overconfidence on lending and leverage in the banking sector before and after the financial crisis | Period: 1994–2009, sample: 1,643 banking-year observations | Option-based |
Hsieh et al. (2014) | Relation between managerial overconfidence and earnings management | Period: 1991–2009, sample: exclusion of, among others, financial firms and regulated firms, sample size varied between 3,748 and 5,499 observations depending on the model | Option-based |
Hsieh et al. (2018) | Relation between managerial overconfidence and tax avoidance | Period: 2004–2014, sample: 1,848 or 1,962 firm-year observations depending on the model | Measure on the basis of purchasing behavior with regard to the shares of the own company following Zheng (2012) |
Hsu et al. (2017) | Relation between managerial overconfidence and conservative or prudent accounting | Period: 1992–2011, sample: 19,386 CEO-year observations | Option-based |
Hsu et al. (2021) | Moderating effect of managerial overconfidence on the relation between book-tax differences and loan contracting | Period: 2001–2017, sample: 6,531 facility-years | Option-based |
Huang et al. (2011) | Relation between managerial overconfidence and cash-flow sensitivity | Period: 2002–2005; sample: exclusion of young enterprises and financial companies, 2,234 firm-year observations of Chinese companies | |
Huang et al. (2016) | Effect of managerial overconfidence on the maturity of financial liabilities | Period: 2006–2012, sample: exclusion of financial companies, 944 listed U.S. companies, 4,309 firm-year observations | Option-based |
Huang-Meier et al. (2016) | Relation between managerial overconfidence and cash | Period: 1992–2010, sample: exclusion of financial companies and utilities, 1,001 firm-year observations in the optimism sample and 4,902 firm-year observations in the non-optimism sample | Option-based and for testing the robustness also measurement based on the investment level |
Hur et al. (2019) | Relation between managerial overconfidence and R&D expenditures | Period: 2011–2017, sample: 6,280 business-years of firms listed on the e Korea Stock Exchange (KSE) and the Korea Securities Dealers Automated Quotation (KOSDAQ) | Measurement based on capital expenditures |
Iyer et al. (2017) | Relation between managerial overconfidence and reactions to a change of CEO | Period: 1994–2011, sample: 470 observations for the liabilities side, 1,626 observations for the equity side | Option-based |
Ji and Lee (2015) | Relation between managerial overconfidence and audit reports with GCO | Period: 2001–2011, sample: 2,742 firm-year observations of 192 FGCO firms and 2,550 CLEAN opinion firms | Measurement based on company characteristics analogous to Schrand and Zechman (2012) |
Kaplan et al. (2012) | Impact of managerial overconfidence on performance in a buyout and venture capitalist context | Period: 2000–2006, sample: 316 candidates considered for CEO positions in firms involved in private equity transactions | Measurement through factor analysis applied to 30 characteristics |
Kim (2013) | Relation between managerial overconfidence and, inter alia, market reactions to takeover announcements | Several sources, including 6,931 interviews of CEOs on CNBC television in the period 1997–2006, CEO change information in the period 1993–2008 | Overconfidence is expressed in the form of self-attribution bias, based on how often CEOs refer to themselves in TV interviews on CNBC or attribute failures to industry or the general economic situation |
Kim and Kim (2019) | Effect of managerial overconfidence on dividend payouts of high performing firms | Period: 1993–2015, sample: 8,801 firm-year observations | Option-based |
Kim et al. (2016) | Relation between managerial overconfidence and a fall in share price | Period: 1992–2010, sample: companies of the S&P 1500 Index, 17,568 year observations (in the case of the second and third measures of overconfidence 16,229 year observations) | |
Kim et al. (2018) | Relation between manager hubris and overinvestment | Period: 1993–2007, sample: 1,914 firm-year observations, 469 companies | Computer-aided text mining of corporate press releases in conjunction with secondary data |
Kim et al. (2021) | Relation between managerial overconfidence on the one hand and firm growth and profitability in the restaurant industry on the other hand | Period: 1993–2016, sample: 148 firm-level panel observations for 27 publicly traded restaurant firms in the United States | Option-based |
Kolasinski and Li (2013) | Impact of strong, independent board members on the takeover activities of overconfident CEOs, learning effects | Period 1988–2006, sample: all mergers and acquisitions carried out in this period based on the acquisition of a majority shareholding, completed and recalled, with a U.S. listed company as acquirer, 15,204 firm-year observations | CEOs are considered overconfident if they buy shares of their company in the secondary market and the shares generate a negative abnormal return within the following 180 days |
Koo and Yang (2018) | Influence of managerial overconfidence on the cash-flow sensitivity of corporate investments | Period: 2007–2013, sample: exclusion of financial and utility companies, 796 firm-year observations with companies within the Korean capital market | Three of the four measures relate to forecast errors, the deviation between forecast and actual earnings (partly based on Lin et al., 2005), while the last measure measures self-attribution bias, triggered by recent corporate success |
Kouaib and Jarboui (2016) | Relation between managerial overconfidence (among others) and R&D expenditures | Period: 2000–2014, sample: 454 CEOs, 182 firms, 2,730 firm-year observations | Score based on Schrand and Zechman (2012) and related to firms’ investing and financing activities |
Kubick and Lockhart (2017) | Relationship between managerial overconfidence and tax policy | Period: 1994–2011, sample: exclusion of financial and utility companies, S&P 1500 companies | Published information on CEO awards through various media channels |
Lai et al. (2017) | Relation between managerial overconfidence and the development of foreign markets | Period: 2001–2004, sample: 1,251 market entries by 782 U.S. companies | Two measures: (1) option-based, (2) media-based |
Lai et al. (2021) | Relation between managerial overconfidence and labor investment efficiency | Period: 1996–2017, sample: 16,766 firm-years | Four measures: three option-based measures, one measure based on excess investment |
Lee (2016) | Relation between managerial overconfidence and weaknesses in internal control mechanisms in financial reporting | Period 2004–2011, sample: companies that disclose weaknesses in their control systems according to the Sarbanes-Oxley Act (SOX), 8,933 firm-year observations, thereof 495 on companies that disclose their weaknesses in the corresponding Section 404 of SOX | Measurement based on company characteristics analogous to Schrand and Zechman (2012) |
Lee (2021) | Relation between managerial overconfidence and voluntary disclosure of greenhouse gas emissions and a moderating role of diversity and industry-level competition on the relation between managerial overconfidence and firm performance | Period: firms in the Korea Stock Exchange (KSE) and the Korea Securities Dealers Automated Quotation (KOSDAQ) listed as of as of 31 December 2019, sample: 13,334 firm-year observations | Measurement by residuals obtained from an estimation of capital expenditure |
Leng et al. (2021) | Relation between managerial overconfidence and the probability of corporate failure | Period: 1999–2017, sample: 1,891 firms, 235 cases of failures | Three measures: (1) share-based measure following Kolasinski and Li (2013), (2) option-based, (3) media-based |
Li and Tang (2010) | Impact of hubris on the risk attitude of Chinese managers | Period: August—October 2000, Sample: questionnaire survey, manufacturing industry with a final sample size of 2,790 enterprises | Difference between the subjective assessment of CEOs (questionnaire survey) and the actual company performance (return on sales). A larger difference in z-scores implies a higher degree of CEO hubris. It should be noted that this measure can target both a personality trait and a cognitive bias. |
Li and Sullivan (2020) | Relation between managerial overconfidence and strategic foresight | Period: first study in 2011 comprising data for 2006–2010, second study in 2012 comprising data from participants of the first study for the year 2011, sample: 498 Chinese firms | Measurement following Li and Tang (2010) |
Lin et al. (2005) | Relations between managerial overconfidence and investments | Period: companies listed on the Taiwan Stock Exchange between 1985 and 2002, sample: exclusion of financial companies, 8,711 forecasts from 386 CEOs in 869 different companies | Measurement based on prediction errors in managers’ earnings forecasts adjusted for specific reasons for prediction errors. It should be noted that this measure can measure both a personality trait and a cognitive bias. |
Lin et al. (2008) | Relation between managerial overconfidence and investments | Period: companies listed on the Taiwan Stock Exchange and over-the-counter market between 1989 and 2004 and found in the Taiwan Economic Journal Database, sample: 1,931 forecasts by 591 CEOs in 511 different companies | Measurement based on prediction errors in managers’ earnings forecasts adjusted for specific reasons for prediction errors (cf. Lin et al., 2005), another measure is based on share ownership. It should be noted here that the first variable can measure both a personality trait and a cognitive bias. |
Lin et al. (2019) | Influence of managerial overconfidence on the recommendation of analysts to investors (selling side), the time taken by analysts to review such stocks and the effect of recommendations on investors depending on managerial overconfidence | Period: 1994–2014, sample: 58,776 revisions of analysts’ recommendations, 37,505 of which are observations on CEO overconfidence | Option-based |
Lin et al. (2020) | Relation between managerial overconfidence and loan spreads | Period: 1993–2015, sample: 16,703 loan contracts of 2,104 publicly listed U.S. firms | Option-based |
Liu and Nguyen (2020) | Impact of managerial overconfidence on CEO letter style | Period: 2014–2016, sample: 1,150 firm-year observations in the unbalanced sample and 1,071 in the balanced sample | Option-based |
Liu and Lei (2021) | Impact of managerial overconfidence on the relation between managerial abilities and stock price crashes | Period: 1994–2018, sample: 24,289 firm-years | Option-based |
Loureiro et al. (2020) | Moderating impact of managerial overconfidence on the relation between CEO 1$ compensation on the one hand und firm performance and total CEO pay on the other hand | Period: 1992–2013, sample: 80 CEOs | Option-based |
Lu et al. (2015) | Relation between REIT managers’ overconfidence and acquisitions | Period: 1983–2007, sample: 1,887 REIT acquisition announcements, 393 acquiring REITs and 1,204 non-acquiring REITs | Measurement based on the buying of shares following Malmendier and Tate (2005) |
Malmendier and Tate (2005) | Impact of managerial overconfidence on corporate investments | Period: 1980–1994, sample: 477 listed U.S. companies | Two option-based measures and one measure based on the fact that overconfidence is expressed by CEOs buying more shares in a company despite existing shareholdings |
Malmendier and Tate (2008) | Managerial overconfidence in company takeovers, consequences and reactions of the market | Period: 1980–1994, sample: 394 listed U.S. companies | Two option-based measured variables and one media-based measured variable |
Malmendier et al. (2011) | Impact of managerial overconfidence on financing policy | Period: 1980–1994, sample: exclusion of financial and utility companies, 477 U.S. listed companies, additional information on birth cohort and military service | Two measures: (1) option-based, (2) media-based |
McManus (2018) | Relation between managerial hubris and profit manipulation | Period: 01.07.2002–30.09.2002, sample: matched-pair structure, including use of the U.S. General Accounting Office’s (GAO) financial restatement database, 142 balance sheet adjustments | Measurement based on media interest, self-importance and pride |
Mitra et al. (2019) | Relation between managerial overconfidence and the cost of auditing the consolidated financial statements, taking into account the impact of the competence of managers and the characteristics of the Board of Directors and the Audit Committee | Period: 2003–2011 (a post-SOX period was deliberately chosen), sample: exclusion of, among others, financial companies and foreign companies (probably non-U.S. companies), 12,942 observations of 2,515 companies with data on audit fees | Three measures, two of which are based on capital expenditure, the third is option-based |
Mueller and Brettel (2012) | Relation between managerial overconfidence, company performance and stock market developments over the business cycle | Period: 1999–2008, sample: 33 listed German companies that rank among the 100 best German companies (World Magazine Ranking), 332 CEO-years of 67 CEOs from 35 companies | Option-based |
Park and Chung (2017) | Possibility of limiting managerial overconfidence by institutional investors | Period: 1992–2010, sample: exclusion of financial and utility companies, companies listed on the New York Stock Exchange, AMEX and NASDAQ, 17,051 firm-year observations | Option-based |
Park and Kim (2009) | Relation between managerial overconfidence and the indebtedness of Korean companies | Period: 1985–2007, sample: exclusion of financial companies, 10,848 yearly observations of 516 listed Korean companies | Based on a questionnaire survey in which managers give their assessment of the current and expected economic situation, the Central Bank of South Korea compiles an index whose average value over the last 12 months is used as an indicator of overconfidence |
Park et al. (2018) | Relation between CEO hubris, corporate performance and corporate structures | Period: 2001–2008, sample: 654 firm-year observations, 164 large Korean companies | Three measures: (1) based on press articles, (2) number of CEO certifications or awards, (3) based on letters from CEOs to shareholders |
Pavićvić and Keil (2021) | Relation between managerial overconfidence and level of acquisition premiums | Period: 2001–2018, sample: 349 acquisitions | Option-based |
Phua et al. (2018) | Relation between managerial overconfidence and the encouragement of stakeholders, employees and suppliers to be more engaged and to make more effort | Period: 1993–2011, sample: exclusion of financial and utility companies, 1,921 companies, 14,754 firm-year observations | |
Pierk (2021) | Relation between managerial overconfidence and write-offs following CEO turnover | Period: 1993–2012, sample: 1,175 CEO changes, 11,642 firm-year observations | Three measures: One option-based measure and two investment-based measures following Ahmed and Duellman (2013) |
Reyes et al. (2020) | Moderating impact of the business cycle on the positive relation between managerial overconfidence and firm performance | Period: 1992–2015, sample: 220 industries, 1,712 companies, 15,217 firm-year observations | Option-based |
Rovenpor (1993) | Importance of CEO self-confidence (in the sense of overconfidence) and other personality traits for corporate takeover activities | Sample: The target group were CEOs of the 350 top companies according to the 1988 Fortune 500 list of the largest industrial companies and the CEOs of the 150 top companies according to the 1988 Fortune 500 list of the largest service companies. The final sample included CEOs of 269 of these companies. | Self-confidence was measured by content analysis in CEO speeches and in a questionnaire using two items from Rotter’s Locus of Control Scale (1966) |
Sauerwald and Su (2019) | Relation between managerial overconfidence and the difference between what companies communicate in terms of CSR and what they actually implement | Period: 2006–2014, sample: S&P 500 companies, 1,003 observations | Option-based |
Schrand and Zechman (2012) | Influence of managerial overconfidence on misstatements in financial reporting | Period: January 1996–2003, 49 court-ordered audits due to misrepresentations in financial reporting, and for further analysis, use of a sample from the high-tech industry and a sample covering different industries | Several measures of overconfidence are used, including aspects of remuneration, start-up experience and expertise |
Schumacher et al. (2020) | Impact of managerial overconfidence on the relation between performance feedback and risk-taking | Period: 1992–2014, sample: 5,482 firm-year observations for 824 distinct firms | Two measures: (1) option-based, (2) media-based |
Seo and Sharma (2018) | Relation between share-based compensation and risk appetite in the U.S. restaurant industry, with managerial overconfidence as a moderator | Period: 1992–2013, sample: 659 firm-year observations from 45 U.S. restaurant companies | Option-based |
Seo et al. (2017) | Relation between managerial overconfidence and the maturity of liabilities | Period: 1992–2015, sample: U.S. listed restaurant companies, 791 firm-year observations, 45 restaurant companies | Option-based |
Simon and Houghton (2003) | Relation between managerial overconfidence and groundbreaking product launches at smaller companies in the computer industry | Sample: 135 companies in Georgia which introduced a new product shortly before the survey | Overconfidence refers to the managers’ conviction that the new product will be successful. For this purpose, interviews were conducted in which the managers were asked to explicitly state which success factors are important for their products. The statements of the managers were then coded according to their choice of words and compared with the findings of the questionnaire survey 18 months after the product launch and a measure was calculated from this. |
Tan (2017) | Relation between managerial overconfidence and financing preferences in U.S. real estate investment companies | Period: 1992–2014, sample: issue of 100 debt instruments and 189 shares of 62 real estate investment companies | Option-based |
Tang et al. (2015a) | Relation between CEO hubris and the innovation policy of companies | 1st study: cross-sectional data on CEOs of 2,820 Chinese manufacturing companies, data from a questionnaire survey conducted in 2000; 2nd study: longitudinal data on U.S. listed high-tech companies, period: 1995–2005, 3,285 firm-year observations | 1st study: Difference between the subjective assessment of CEOs (questionnaire survey) and the actual company performance (return on sales), 2nd study: CEO hubris measure based on forecast errors. It should be noted that the variables can measure both a personality trait and a cognitive bias. |
Tang et al. (2015b) | Relation between manager hubris and CSR | Period: 2001–2010, sample: 1,925 firm-year observations, 464 CEOs, 397 companies from the S&P 1500 companies | Media-based |
Tang et al. (2018) | Different relations between CEO hubris versus CEO narcissism and CSR activities | Period: 2003–2010, sample: 266 CEOs, 235 U.S. companies listed in the S&P 1500, 769 firm-year observations | Media-based |
Tebourbi et al. (2020) | Relation between managerial overconfidence and R&D investments | Period: 2007–2016, sample: 2,051 firm-year observations of Vietnamese firms | Measurement based on residuals of the regression of investment, i.e. the sum of capital expenditures, R&D expense, and acquisitions minus sale proceeds of property, plant, and equipment divided by lagged total assets, on lagged change in sales |
Ting et al. (2016) | Relation between managerial overconfidence and financing preferences | Sample: 1,404 firm-year observations of 793 companies listed on the Malaysian stock exchange as of 30.09.2012 | Six measures: (1) size of the CEO photo in the annual report, (2) educational background, (3) wealth of experience, (4) gender, (5) network, (6) performance |
Vivian and Xu (2018) | Managerial overconfidence and the “pecking order” | Period: 1994–2011, sample: 2,283 observation points, 459 British companies | Three measures: (1) a computer-based linguistic analysis of the statements of the decision-makers analyzed, whether they are written in an optimistic tone, (2) an industry-adjusted investment based measure (similar to Campbell et al., 2011), (3) how CEOs and CFOs deal with their shareholdings |
Wang et al. (2016) | Relation between inflation uncertainty, managerial overconfidence and investment behavior | Period: 2003–2012, sample: exclusion of financial companies, 2,332 Chinese companies | Measurement using the difference between predicted and actual success figures according to Lin et al. (2005). It should be noted that this measure can target both a personality trait and a cognitive bias. |
Wang et al. (2018) | Relation between political relations, the level of investment in R&D and managerial overconfidence | Period: 2010–2014, sample: 1,293 Chinese companies listed on the Shanghai or Shenzhen stock exchange | A comparative analysis of the investment flows of the sample companies regarding the highs and lows of the Chinese business cycle and the investment behavior of peer group companies allows to determine overconfidence, since the investment behavior of the self-confident managers deviates from an optimal behavioral pattern closely related to the business cycle. |
Wong and Wang (2018) | Effect of managerial overconfidence on the valuation of investments in TV commercials by the stock market and the impact of family ownership on it | Period: 2007–2011, sample: 1,658 announcements of new TV spots by 78 companies listed on the Taiwanese stock exchange | Media-based |
Yang (2015) | Relation between manager hubris in mergers and cost remanence | Period: 1995–2011, sample: 303 mergers, 1,786 control companies | CEO hubris on the bidder side is determined via an interaction variable consisting of the dummy variable BidderHubris, which takes the value one if the company is a merged company, and the variable Optimism, which captures the deviation of the manager’s sales forecast from the actual sales figures |
Zavertiaeva et al. (2018) | Influence of managerial overconfidence on innovation activity of the company, investment in R&D, its output and impact on goodwill | Period: 2008–2013, sample: transnational sample of 766 listed European companies | Three measures: (1) CEOs named in press reports, (2) their age, (3) their experience |
Zhang et al. 2020 | Impact of managerial overconfidence on firm pollution | Period: 2015–2017, sample: 319 observations for 236 firms | Three measures: two media-based measures and one salary-based measure |
4.2 Managerial overconfidence and material resources
4.2.1 Mergers and acquisitions
4.2.2 Investment behavior and share buybacks
4.2.3 Financing preferences and dividend payments
4.2.4 Tax policy
4.2.5 Reactions of investors, analysts, and lenders
4.2.6 Financial performance
4.3 Managerial overconfidence and social resources
4.4 Managerial overconfidence and procedural resources
4.4.1 Accounting
4.4.2 Auditing
4.4.3 Innovation processes
4.5 Decision-making processes
4.6 CSR
4.7 Moderators
Authors (year) | The connection between overconfidence and… | Moderator | Amplification of adverse effects | Amplification of beneficial effects | Mitigation of adverse effects | Mitigation of beneficial effects | Moderation of neutral relations |
---|---|---|---|---|---|---|---|
Dynamics, uncertainty, complexity and advantageousness of the environment
| |||||||
Ji and Lee (2015) | Critical assessment by the auditor |
High uncertainty
|
X
| ||||
Lai et al. (2017) | Acquisition of a full participation in a foreign company |
High uncertainty
|
X
| ||||
Hsu et al. (2017) | Corporate success (with conservative accounting) |
High uncertainty
|
X
| ||||
Arena et al. (2018) | Environmentally friendly innovations |
High uncertainty
|
X
| ||||
Tang et al. (2015b) | Low awareness of socially responsible activities |
High uncertainty
|
X
| ||||
Tang et al. (2015b) | High perception of socially irresponsible activities |
High uncertainty
|
X
| ||||
Chung and Hribar (2021) | Timeliness of goodwill impairments |
Uncertainty about firm performance
|
X
| ||||
Li and Tang (2010) | Risk behavior |
Great market complexity
|
X
| ||||
Tang et al. (2015a) | Company innovations |
Great environmental complexity
|
X
| ||||
Engelen et al. (2015) | Entrepreneur orientation |
High market dynamics
|
X
| ||||
Tang et al. (2015a) | Company innovations |
A more favorable environment
|
X
| ||||
Li and Tang (2010) | Risk behavior |
Positive market conditions
|
X
| ||||
Galasso and Simcoe (2011) | Innovation |
Strong competition
|
X
| ||||
Tang et al. (2015b) | High perception of socially irresponsible activities |
Strong competition
|
X
| ||||
Li and Sullivan (2020) | Strategic foresight |
Industry concentration
|
X
| ||||
Hirshleifer et al. (2012) | R&D expenditure |
Innovativeness of the industry
|
X
| ||||
Hirshleifer et al. (2012) | Patent applications |
Innovativeness of the industry
|
X
| ||||
Hirshleifer et al. (2012) | Patent citations |
Innovativeness of the industry
|
X
| ||||
Lai et al. (2017) | Acquisition of a full participation in a foreign company |
Information asymmetry
|
X
| ||||
Lai et al. (2017) | Acquisition of a full participation in a foreign company |
Cultural distance
|
X
| ||||
Lai et al. (2017) | Acquisition of a full participation in a foreign company |
Institutional distance
|
X
| ||||
Hsu et al. (2017) | Corporate success (with conservative accounting) |
Less restrictive financing conditions
|
X
| ||||
Ownership
| |||||||
Wong and Wang (2018) | Adverse evaluation of a new TV advertising campaign by investors |
Family participation
|
X
| ||||
Ting et al. (2016) | Financial decision |
State participation
|
X
| ||||
Li and Tang (2010) | Risk behavior |
State participation
|
X
| ||||
Supervisory bodies and accounting
| |||||||
Lai et al. (2017) | Acquisition of a full participation in a foreign company |
Strong board
|
X
| ||||
Kolasinski and Li (2013) | Value-destroying takeover activity |
Strong board
|
X
| ||||
Brown and Sarma (2007) | Value-destroying takeover activity |
Strong board
|
X
| ||||
Park et al. (2018) | Lower business success |
Strong board
|
X
| ||||
Mitra et al. (2019) | Audit costs |
Strong board
|
X
| ||||
Chung and Hibrar (2021) | Timeliness of goodwill impairments |
Strong board
|
X
| ||||
Bouzouitina et al. (2021) | CSR activities |
Corporate governance effectiveness
|
X
| ||||
Hayward and Hambrick (1997) | Acquisition premium |
CEO also chairman of the board
|
X
| ||||
Li and Tang (2010) | Risk behavior |
Board membership of the CEO
|
X
| ||||
Hayward and Hambrick (1997) | Acquisition premium |
High number of internal board members
|
X
| ||||
Sauerwald and Su (2019) | Decoupling between communicated and actual CSR commitment |
Expertise of external board members
|
X
| ||||
Sauerwald and Su (2019) | Decoupling between communicated and actual CSR commitment |
Shares of external board members in the company
|
X
| ||||
Ahmed and Duellman (2013) | Conservative accounting |
External monitoring (
no effect
)
|
x
| ||||
Chen and Lu (2015) | Low success of share buybacks |
Corporate governance
|
X
| ||||
Cormier et al. (2016) | Misconduct |
Corporate governance (
no effect
)
|
x
| ||||
Kim et al. (2016) | Share price falls |
CEO dominance
|
X
| ||||
Kim et al. (2016) | Share price falls |
Disagreeing investors
|
X
| ||||
Kim et al. (2016) | Share price falls |
Conservative accounting
|
X
| ||||
Park and Chung (2017) | Tendency to overinvestment |
Monitoring by institutional, long-term investors
|
X
| ||||
Mitra et al. (2019) | Audit costs |
Managerial skills
|
X
| ||||
Mitra et al. (2019) | Audit costs |
Effectiveness of the auditor
|
X
| ||||
Introduction of SOX
| |||||||
Banerjee et al. (2015) | Risk behavior |
SOX
|
X
| ||||
Banerjee et al. (2015) | Low dividend payments |
SOX
|
X
| ||||
Banerjee et al. (2015) | Little success with company takeovers |
SOX
|
X
| ||||
Banerjee et al. (2015) | Low business success |
SOX
|
X
| ||||
Banerjee et al. (2018) | Shareholder class actions |
SOX
|
X
| ||||
Hsieh et al. (2014) | Earnings management |
SOX
(little effect)
|
x
|