Managers Self-Inclusive Language in Conference Calls: Multi-Method - PowerPoint PPT Presentation

Managers’ Self-Inclusive Language in Conference Calls: Multi-Method Evidence Zhenhua Chen Serena Loftus Tulane University March 2017

Research Question • How do investors react to managers’ SIL? • SIL: self-inclusive language – Statements that explicitly include the speaker – Two types: • Individual: I, me, mine • Collective: We, us, ours

Managers and SIL I

Managers and SIL We

Managers and SIL SEL

Managers and SIL SEL ?

Motivation SIL • Role in impression management • SIL processed automatically in brain – Suggests investors cannot “unwind” SIL (Kimbrough and Wang 2014; Cianci and Kaplan 2010) • Managers have some latitude to substitute SIL – Can use SIL vs. SEL or collective vs. individual SIL

Examples of SIL in impression management More collective SIL after 9/11 (Pennebaker and Lay 2003)

Examples of SIL in impression management “As silly as it sounds, pronouns matter. Whenever possible...substitute ‘we’ for ‘I.’” – Sheryl Sandberg, Chief Operating Officer of Facebook in her book Lean In

Contribution • SIL can play a role in impression management – Complements Cho, Roberts and Patten 2010; García Osma and Guillamón-Saorín 2011; Merkl-Davies, Brennan and McLeay 2011; Kimbrough and Wang 2014 • Function language impacts investors – Complements research focused on content language (Li 2008; Davis, Pigor and Sedor 2012; Hales, Kuang and Venkataraman 2011; Loughran and McDonald 2011) • Traditional attribution theories may not apply to managers – Aerts 2005; Merkle-Davis and Brennan 2011; Clatworthy and Jones 2003 • Multiple research methods to complement findings – Address concerns by Koonce and Mercer 2005; Li 2011; answers call from Bloomfield, Nelson and Soltes 2016

Institutional Background: Language • Growing research investigating managers’ language Two Types of Language Function Content Language Language Is the “…linguistic glue used to hold content words together.” Used to convey content or meaning (Groom and Pennebaker 2002) (e.g., nouns, adjectives, verbs) (e.g., pronouns, articles, conjunctions, etc.)

Real-World Example “Through our expansion program, we're positioning ourselves for the surge in prescription use that's already underway. And we anticipate getting a bigger slice of that growing pie. The demographics isn't the only thing we have going for us. Our financial position is stronger than it's ever been. We're generating strong cash flow from operations. We have virtually no debt. We have nearly $300 million in the bank, and $3 billion in owned real estate. We're growing in a down economy, and our superior real estate gives us a dramatic competitive edge. Bottom line, we're excited about what we can accomplish during fiscal 2003.” – Rick Hans, Director of Finance, Walgreen’s (1/3/2003; $0.01 + ES)

Real-World Example “Through our expansion program, we're positioning ourselves for the surge in prescription use that's already underway. And we anticipate getting a bigger slice of that growing pie. The demographics isn't the only thing we have going for us. Our financial position is stronger than it's ever been. We're generating strong cash flow from operations. We have virtually no debt. We have nearly $300 million in the bank, and $3 billion in owned real estate. We're growing in a down economy, and our superior real estate gives us a dramatic competitive edge. Bottom line, we're excited about what we can accomplish during fiscal 2003.” – Rick Hans, Director of Finance, Walgreen’s (1/3/2003; $0.01 + ES) – Readability (FOG) score: 11.5 – Affect: 4%

Real-World Example “Through our expansion program, we're positioning ourselves for the surge in prescription use that's already underway. And we anticipate getting a bigger slice of that growing pie. The demographics isn't the only thing we have going for us. Our financial position is stronger than it's ever been. We're generating strong cash flow from operations. We have virtually no debt. We have nearly $300 million in the bank, and $3 billion in owned real estate. We're growing in a down economy, and our superior real estate gives us a dramatic competitive edge. Bottom line, we're excited about what we can accomplish during fiscal 2003.” – Rick Hans, Director of Finance, Walgreen’s (1/3/2003; $0.01 + ES) – 54% Function Language – 15% Collective SIL

Institutional Background: Use of SIL • Archival analysis of over 50,000 earnings conference calls • SIL approximately 6.7% of words spoken • Substantial variation in SIL: – 3.51% at 1% – 9.81% at 99% • Support for substitution of individual/collective SIL – Negative correlation coefficient (-0.12; p = 0.01) • Overall, SIL material portion of managers’ remarks

H1 Perceptions of + + SIL Investment Controllability • Explicit attributions have been shown to increase perceptions of managers’ controllability – e.g., Elliott, Hodge and Sedor 2011 • Our innovation: SIL increases perceptions of controllability – Even when not in attributions – Gives the impression the manager is associated with outcomes

H1 Perceptions of + + SIL Investment Controllability • Normally, perceptions of control moderated by outcomes – Crant and Bateman 1993 • For CEOs, high controllability always positive regardless of news – Siegel and Brockner 2005; Lee, Peterson and Tiedens 2004 • High controllability for negative events creates impression CEO is more in control of future events – Lee and Robinson 2000; Salancik and Meindl 1984

H1 Perceptions of + + SIL Investment Controllability H1a: Investors will react more positively to disclosures containing high SIL than low SIL (regardless of news).

Research Design • Use experiment to test H1: strong causal evidence • 2 x 2 between-subjects design with manipulated variables: – Language (pooled): SIL, SEL – News: Good, Bad • 491 Amazon.com Mechanical Turks complete study – Appropriate proxies for RQ – 236 participants fail at least one comprehension check question – 3 comprehension check questions: identify news, identify name of CEO, identify correct EPS forecast • Most of the comprehension check failures are clustered by participant and occur on the news question (statistically more in the bad news condition) – 255 participants included in final sample for hypothesis testing • Participants earn $1.80 flat wage

Manipulation (Recorded by Voice Actor) (I am/We are/Webtex is) [pleased/disappointed] to announce second-quarter earnings for the 2016 fiscal year of $6 per share, which consists of revenue of $182,795 and net income of $39,510. (I/We/Management) had expected earnings per share of [$5/$7], so our (Webtex’s) earnings are [higher/lower] than (my/our/management’s) forecast by $1 per share. (My/Our/Management’s) earnings forecast was based on Webtex’s net income from the second-quarter of the last fiscal year, which means that Webtex’s current earnings are [higher/lower] than second-quarter earnings for the 2015 fiscal year. As (I/we/Webtex’s managers) look ahead to the next quarter, (I am/we are/ management is) very optimistic about Webtex’s future. (I am/We are/ Management is) currently forecasting earnings-per-share of $6.75 for the next quarter, which is the third quarter of the 2016 fiscal year. (I/We/Webtex’s managers) want to thank you for your continued support of Webtex. This concludes (my/our/management’s) comments for the quarter.

Experimental Flow (2-stage design) Listen to Receive conference call Answer Answer information excerpt dependent demographic about a containing variable questions fictional firm language and questions Webtex news manipulation Read letter to shareholder Within-Subjects containing Answer Follow-up Experiment fully-crossed supplemental 1 x 2 questions Language manipulation

Results (Figure 1 Panel A) 80 SIL > SEL: F=3.53; p < 0.03, one-tailed 70 Likelihood 60 SEL 50 SIL 40 30 20 Good News Bad News

Results (Table 2) Panel B: Analysis of variance Dependent Source of Sum of Mean Variable Variation Squares d.f. Square F-Statistic p -value Likelihood SIL 1598.72 1 1598.72 3.53 0.06 News 28950.53 1 28950.53 63.97 <0.01 SIL x News 122.71 1 122.71 0.27 0.60 Error 113591.3 251 452.44 Investment SIL 17216633 1 17216633 3.74 0.05 News 77634350 1 77634350 16.88 <0.01 SIL x News 2639716 1 2639716 0.57 0.45 Error 1.16E+09 251 4599968

Results (Table 2) Panel A: Descriptive Statistics [standard deviations] Language News n Likelihood Investment 3,144.07 Good 42 67.10 [21.47] [2,469.16] SEL 1,057.74 Bad 31 26.81 [16.91] [1,018.46] 3,909.32 Good 98 74.47 [20.57] SIL [2,530.71] (I + We) 1,368.71 [ Bad 84 31.08 [23.30] 1,743.39] Within SIL: 4,117.25 Good 55 76.42 [19.95] [2,586.02] I 1,542.84 Bad 45 35.91 [23.83] [1,963.10] 3,643.35 Good 43 71.98 [21.31] [2,462.54] We 1,167.79 Bad 39 25.51 [21.66] [1,448.84]

Exploratory Analysis of SIL Type (Figure 1 Panel B) 80 70 Likelihood 60 SEL 50 I 40 We 30 20 Good News Bad News