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This paper develops a typology of argumentation strategies used in lobbying. Unlike in other strategic communication functions such as crisis or risk communication, such typologies have not been proposed in the sub-field of public affairs.

The article synthesises the strategic communication, political communication and policy studies literature and employs exchange theory to explain the communicative-strategic exchange in public affairs. It showcases its explanatory potential with illustrative examples from Big Tech lobbying.

The paper describes that categories of argumentation strategies that a public affairs professional will choose are based on the contingency of the issue, policy objective and lobbying objective. The descriptive typology will require empirical testing to develop further.

The paper describes how public affairs professionals influence public policy through their argumentation strategies, which sheds light on the usually opaque activities of lobbying.

The proposed typology is the first of its kind for the field of public affairs. Beyond, it contributes communication-scientific insights from a rhetorical tradition to strategic communication research and other social science fields where lobbying is studied, e.g. policy studies.

Research on artificial intelligence (AI) and its potential effects on the workplace is increasing. How AI and the futures of work are framed in traditional media has been examined in prior studies, but current research has not gone far enough in examining how AI is framed on social media. This paper aims to fill this gap by examining how people frame the futures of work and intelligent machines when they post on social media.

We investigate public interpretations, assumptions and expectations, referring to framing expressed in social media conversations. We also coded the emotions and attitudes expressed in the text data. A corpus consisting of 998 unique Reddit post titles and their corresponding 16,611 comments was analyzed using computer-aided textual analysis comprising a BERTopic model and two BERT text classification models, one for emotion and the other for sentiment analysis, supported by human judgment.

Different interpretations, assumptions and expectations were found in the conversations. Three subframes were analyzed in detail under the overarching frame of the New World of Work: (1) general impacts of intelligent machines on society, (2) undertaking of tasks (augmentation and substitution) and (3) loss of jobs. The general attitude observed in conversations was slightly positive, and the most common emotion category was curiosity.

Findings from this research can uncover public needs and expectations regarding the future of work with intelligent machines. The findings may also help shape research directions about futures of work. Furthermore, firms, organizations or industries may employ framing methods to analyze customers’ or workers’ responses or even influence the responses. Another contribution of this work is the application of framing theory to interpreting how people conceptualize the future of work with intelligent machines.

This paper aims to investigate a condition under which identity salience effects are weakened. By examining how identity salience influences individuals’ product judgment in a domain of trade-offs, the current research demonstrates that the utilitarian value of a product is an important determinant of the effectiveness of identity salience on product judgment.

This research consists of two experiments. In Experiment 1, the authors examined whether identity salience effects were mitigated when the level of the perceived utilitarian value of an identity-incongruent product was greater than that of an identity-congruent product. In Experiment 2, the authors examined the effectiveness of internal attribution as a moderator that strengthens identity salience effects when the perceived utilitarian value of an identity-incongruent (vs. identity-congruent) product is higher.

In Experiment 1, the authors show that when the utilitarian value of a product with an attribute congruent (vs. incongruent) with one’s salient identity is lower, individuals do not show a greater preference for the identity-congruent (vs. identity-incongruent) product, mitigating the identity salience effects. Experiment 2 demonstrates that when individuals with a salient identity attribute a decision outcome to the self, they display a greater preference for the identity-congruent product even when its utilitarian value is lower compared to that of the identity-incongruent product.

The research contributes to previous research examining conditions under which identity salience effects are weakened [e.g. social influence by others (Bolton and Reed, 2004); self-affirmation (Cohen et al., 2007)] by exploring the role of the utilitarian value of a product, which has not been examined yet in prior research. Also, by doing so, the current research adds to the literature on identity salience in a domain of trade-offs (Benjamin et al., 2010; Shaddy et al., 2020, 2021). Finally, this research reveals that when a decision outcome is attributed to the self, identity salience effects become greater. By finding a novel determinant of identity salience effects (i.e. internal attribution), the present research contributes to the literature that has examined factors that amplify identity salience effects [e.g. cultural relevance (Chattaraman et al., 2009); social distinctiveness (Forehand et al., 2002); different types of groups (White and Dahl, 2007)].

The findings provide managerial insights on identity-based marketing by showing a condition under which identity-based marketing does not work [i.e. when the utilitarian value of an identity-congruent (vs. identity-incongruent) product is lower] and how to enhance the effectiveness of identity-based marketing by using internal attribution.

By exploring the role of utilitarian value, not yet examined in prior research, the present research adds to the knowledge of the conditions under which identity salience effects are weakened. Furthermore, by finding a novel determinant of identity salience effects (i.e. internal attribution), the research contributes to the literature on factors that amplify identity salience effects.

Endorsement marketing has been widely used to generate consumer attention, interest and purchase decisions among targeted audiences. Internet celebrities who become famous on the Internet are dependent on strategic intimacy to appeal to their followers. Our study aims to examine how multiple exposures to Internet celebrity endorsements influence consumers’ click and purchase decisions in the context of influencer marketing.

Based on a unique and representative dataset, the authors first model consumers’ choices for clicks and purchases with two panel fixed-effect logit models linking clicks and purchases with the frequency of exposure to Internet celebrity endorsement. To further control the endogeneity produced by the intercorrelation between the click and purchase models, the authors also adopt the two-stage Heckman probit structure to jointly estimate the two models using Maximum Likelihood Estimation. Robustness checks confirm the effectiveness of the models.

The results suggest that Internet celebrity endorsement plays a significant role in bringing referral traffic to e-commerce sites but is less helpful in affecting conversion to sales. The impact of repetitive Internet celebrity endorsements on consumers’ click decisions is U-shaped, but the role of Internet celebrities as online retailers will “shape-flip” this relationship to a negative linear relation.

Our study is the first to investigate the repetitive exposure effect of Internet celebrity endorsement. The results show a contradictory pattern with a wear-out effect of repetition in the advertising literature. This is the first study to show how the endorsing self, which is a common business model in influencer marketing, moderates the effectiveness of influencer marketing.

This paper aims to investigate the mechanisms through which social media news consumption across different platforms leads to opinion polarization in society. To this end, the authors draw from cultivation theory to examine whether social media news consumption imparts a mainstreaming or resonance effect. Media consumption imparts a mainstreaming effect if frequent users, regardless of their social identity, develop homogenous attitudes about issues, whereas resonance is at play if there is a differing cultivation effect on various social groups depending on their relatability of life experiences.

The authors conduct the study in the developing context of India, using a population survey dataset from 2019. Regression-based mediation and moderation analyses were carried out to test the hypotheses.

The findings reveal that resonance is the most prominent mechanism through which social media news consumption cultivates opinion polarization, contrary to the mainstreaming effect imparted by television. Further, WhatsApp use was found to strengthen the polarizing effect of overall social media news consumption, while YouTube use weakened the cultivation of polarization.

The paper unearths how social media news consumption influences the opinion polarization of various social groups differently. The authors also find the differential effect of specific platform use. These findings have the potential to inform policymakers and developers about how to mitigate the detrimental effects of platform-based political persuasion.

This study offers significant contributions. First, the authors explain social media-induced polarization using the novel theoretical lens of cultivation. Second, the authors find that social media and television news consumption differ in their polarizing effects. Third, the authors find that while WhatsApp use amplifies the polarizing effect of social media news consumption, YouTube use weakens it.

The efficient application of building information modeling (BIM) methodology in the sustainable building design process, known as green BIM, provides ideal leverage to significantly enhance multidiscipline team collaboration. However, the practical execution of green BIM is characterized by issues such as duplication of work, information silos and poor cross-party coordination. Besides, there are limited studies on the specific components that are critical to driving green BIM collaborative design. This study aims to establish the critical components of green BIM collaborative design to enable the multidiscipline team to effectively use diverse software to collaboratively exchange accurate information, thus ensuring informed decision-making in the sustainable building design process.

Data were obtained by using a questionnaire to survey 360 respondents comprising mainly architects and engineers (civil, mechanical and electrical) in Malaysia. Subsequently, data were analyzed via confirmatory factor analysis. Afterward, a measurement model was established and used to test the 11 hypotheses of this study.

A covariance-based structural equation model of the critical components for successful BIM-based sustainable building design collaboration was established.

The research findings will guide the multidisciplinary team to collaboratively exchange accurate information in green BIM practices.

To the best of the authors’ knowledge, this research is the first attempt in the literature to provide a pragmatic approach for practitioners to combine the established critical components of green BIM to collaboratively exchange heterogeneous sustainability criteria and efficiently design buildings with high sustainability performance, particularly in emerging countries like Malaysia.