The motivation of mission statements: How regulatory mode influences workplace discrimination

Kanze, Dana; Conley, Mark; Higgins, E. Tory

doi:10.1016/j.obhdp.2019.04.002

Cited by 30 publications

(48 citation statements)

References 98 publications

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“…To do this, we collected the inaugural addresses of all presidents from Franklin Roosevelt in 1933 to Donald Trump in 2016, as the former historical moment is considered the point when the two parties established the constituencies they largely still represent today (Chambers and Burnham 1967;Peters n.d.). Following procedures for operationalizing variables from text, which we detail in our main study, we used the regulatory mode dictionary (Kanze, Conley, and Higgins 2019) to measure the regulatory mode language of each inaugural address. We then conducted a t-test to determine differences in regulatory mode language between parties.…”

Section: Methodsmentioning

confidence: 99%

“…Mathmann et al (2017) also used exposure to advertisements featuring assessment language to create a fit effect in consumers, who went on to value choices from larger assortments. Situational inductions of regulatory mode can therefore be induced by environmental cues (Kanze, Conley, and Higgins 2019). For example, regulatory mode orientation expressed through a company's mission statement can create an organizationally induced regulatory mode orientation among its employees (Kanze, Conley, and Higgins 2019), affecting how they support or avoid instances of company discrimination.…”

Section: Situational Influencesmentioning

confidence: 99%

“…When encouraging their followers to pursue electoral and public policy goals, parties use language that innately implies the goal pursuit strategies (i.e., language that implies how goals are pursued) that their followers should use to achieve them. Take, for example, posts written in the language of action (Kanze, Conley, and Higgins 2019), such as a tweet by President Barack Obama encouraging his supporters to be "Fired up! Ready to go!"…”

mentioning

confidence: 99%

“…While not outlining a specific call to action for its audience, the content was designed to energize followers to become active participants in his campaign movement, thereby supporting his goal of reelection. Another common form of content is written in the language of assessment (Kanze, Conley, and Higgins 2019), such as a post written by Obama after he had left office. Here, he encouraged followers to engage in the pursuit of identifying solutions to key policy problems by deliberating on "thought-provoking" (Obama 2019) material about their causes.…”

mentioning

confidence: 99%

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Power and the Tweet: How Viral Messaging Conveys Political Advantage

Crow¹,

Galande²,

Chylinski³

et al. 2021

Journal of Public Policy & Marketing

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Researchers are increasingly confronting the need to examine the impacts of social media on democratic discourse. Analyzing 55,560 tweets from the official Twitter accounts of the Democratic and Republican parties in the United States, we examine approaches used by political parties to encourage sharing of their content within the contemporary political divide. We show that tweets sent by the Republican Party are more likely to be predominant in the language of assessment and that tweets predominant in the language of assessment lead to more retweets. Further, this effect is reduced as political parties gain control of successive branches of government. This is because successive increases in political power create fewer impediments to the implementation of a party’s political agenda. As impediments to action are reduced, so is regulatory fit for assessment-oriented language. Goal pursuit language shared on Twitter therefore reveals distinct approaches to obtaining and dealing with power across the U.S. political system, and constitutes an important tool for public policy makers to use in successfully conducting policy debates.

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Section: Methodsmentioning

confidence: 99%

Section: Situational Influencesmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Power and the Tweet: How Viral Messaging Conveys Political Advantage

Crow¹,

Galande²,

Chylinski³

et al. 2021

Journal of Public Policy & Marketing

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“…The sentence has three content words ("wanted," "cup," and "coffee") which convey the central meaning of the sentence. Psychologists have developed dictionaries to capture content relating to specific psychological themes such as emotion (i.e., positive and negative emotion), cognitive processes (Pennebaker et al, 2015), moral values (Graham et al, 2009), psychological motivations (Stone et al, 1966), well-being (Ratner et al, 2019), regulatory focus (Kanze et al, 2019), markers of suicidal ideation (Thomas & Duszynski, 1985), and even brand personality (Opoku et al, 2008).…”

Section: Content Words and Function Wordsmentioning

confidence: 99%

Text Analysis for Psychology: Methods, Principles, and Practices

Kennedy¹,

Ashokkumar²,

Boyd³

et al. 2021

Preprint

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Due to the explosion of new sources of human language data and the rapid progression of computational methods for extracting meaning from natural language, language analysis is a promising, though complicated, category of psychological research. In this chapter, we give a modern perspective on language analysis as it applies to psychology, uniting historical context, the diverse range of domains studied in psychology via language, and the methodological rigor of natural language processing (NLP) and machine learning. Top–down methods (e.g., dictionary approaches, text annotation) are presented alongside bottom–up methods (e.g., topic modeling, word embedding, language modeling) in order to give the reader a comprehensive grounding in the tools available and the recommended practices involved in applying them. We conclude with a view of the future of language analysis, specifically the ways in which psychology and NLP will continue to co-develop.

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How regulatory focus–mode fit impacts variety‐seeking

et al. 2022

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Variety-seeking research has examined antecedents in terms of contextual factors and individual differences. However, it does not consider the interaction of individual difference factors such as regulatory focus (promotion vs. prevention) and regulatory mode (locomotion vs. assessment) to predict variety-seeking.Drawing on regulatory fit theory, this study introduces a new kind of regulatory fit based on the interaction between regulatory focus and mode (i.e., regulatory focusmode fit), thereby extending previous work examining fit based on either regulatory focus or regulatory mode in isolation. Results from five studies, including field data from 10,547 music app consumers (text analysis), two preregistered studies, and two online experiments, show that regulatory focus-mode fit (vs. non-fit) decreases variety-seeking. Engagement and attitude certainty serially mediate regulatory focus-mode fit effects. Findings provide implications for consumer segmentation and message framing.

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The motivation of mission statements: How regulatory mode influences workplace discrimination

Cited by 30 publications

References 98 publications

Power and the Tweet: How Viral Messaging Conveys Political Advantage

Power and the Tweet: How Viral Messaging Conveys Political Advantage

Text Analysis for Psychology: Methods, Principles, and Practices

How regulatory focus–mode fit impacts variety‐seeking

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