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This paper aims to investigate the effect of product-related description abstractness/concreteness on perceived trustworthiness and the role of consumer product expertise and shopping-stage mindset in the persuasiveness of abstract vs concrete product descriptions.

Two online experiments were conducted: Study 1 (description abstractness – manipulated between-subject; consumer product expertise, perceived trustworthiness, purchase intent – measured), Study 2 (consumer shopping-stage mindset – manipulated between-subject; description abstractness – manipulated within-subject; consumer product expertise, perceived trustworthiness, abstract/concrete description preference – measured).

The negative effect of the abstractness (abstract descriptions vs the ones supplemented with relevant product details) on description trustworthiness was evidenced in Study 1. Trustworthiness was positively related to purchase intent, especially for high product expertise. Study 2 replicated the effect of product description abstractness on its trustworthiness in terms of two other forms of abstractness (abstract descriptions vs the ones supplemented with irrelevant product details and product benefits vs attributes). The goal-oriented (vs comparative) mindset had a positive effect on the benefit (vs attribute) description preference, especially for high product expertise.

For marketers, the results suggest the positive consequences of presenting concrete information on product attributes and the conditions enhancing the effectiveness of presenting product benefits.

The paper integrates the existing views on consumer response to abstract vs concrete information (lexical abstractness/concreteness, means-end chain theory) and links them to consumer product expertise and shopping-stage mindset.

This research investigates consumer intention to follow online community advice. Applying the technology acceptance model (TAM) to the context of online restaurant communities, the study empirically examines the effects of perceived usefulness, perceived ease of use, attitude and trust on the intention to follow online advice.

The data were collected from 360 members of online restaurant communities on Facebook and analyzed using structural equation modeling (SEM).

The findings revealed that trust, perceived usefulness and attitude are key predictors of the intention to follow online restaurant community advice.

Extant research on the influence of online reviews on consumer behavior in the restaurant industry has largely focused on the characteristics of the review, reviewers or readers. Moreover, other studies have investigated consumers' motivations to write online restaurant reviews. This study, however, takes a different approach and examines what drives consumers to follow the advice from online restaurant communities.

Firms employ various forms of disclosure to demonstrate commitment to and involvement in sustainable supply chain management (SSCM) practices. This research provides guidance to firms employing framing strategies when communicating their SSCM with external stakeholders like consumers as part of their supply chain transparency efforts.

The authors employed a middle-range theorizing approach to understand the context of SSCM practices and mechanisms of variously framed communication methods to disclose sustainability information to consumers. The authors conducted two experiments in an e-waste recycling context, studying how sustainable information disclosed to consumers using attribute framing and goal framing can affect consumers' attitudes. The authors also examined the moderating role of consumers' environmental involvement.

Results suggest that when attribute framing is used, firms should avoid framing the attribute from a negative valence. When goal framing is used, messages with consequences stated as “avoid loss” yield the most substantial effect. Additionally, framing effects are more significant for consumers with higher-than-average environmental involvement.

The authors’ results contribute to the ongoing theorization of SSCM by providing contextual understanding of how to communicate sustainability information. Corroborating evidence from marketing, framing effects are found to be context specific, thereby elucidating the framing literature more fully to the SSCM context. The authors extend this literature by studying attribute framing and comparing the effectiveness of all possible goal framing combinations of valence and gain/loss perspective in the SSCM communication context.

Increasing demand on rail transport speeds up the introduction of new technical systems to optimize the rail traffic and increase competitiveness. Remote control of trains is seen as a potential layer of resilience in railway operations. It allows for operating and controlling automated trains and communicating and coordinating with other stakeholders of the railway system. This paper aims to present the first results of a multi-phased simulator study on the development and optimization of remote train driving concepts from the operators’ point of view.

The presented concept was developed by benchmarking good practices. Two phases of iterative user tests were conducted to evaluate the user experience and preferences of the developed human-machine-interface concept. Basic training requirements were identified and evaluated.

Results indicate positive feedback on the overall system as a fallback solution. HMI elicited positive emotions regarding pleasure and dominance, but low arousal levels. Train drivers had more conservative views on the system compared to signalers and students. The training activities achieved increased awareness and understanding of the system for future operators. Inclusion of potential users in the development of future systems has the potential to improve user acceptance. The iterative user experiments were useful in obtaining some of the needs and preferences of different user groups.

Multi-phase user tests were conducted to identify and to evaluate the requirements and preferences of remote operators using a simplified HMI. Training analysis provides important aspects to consider for the training of future users.

Modern intra- and inter-organizational arrangements require firms to cross boundaries, but this process represents a crucial and complex challenge, especially for organizations that face pluralistic tensions. Scholars still lack sufficient knowledge of how boundaries can be crossed and what kind of boundary management is necessary within pluralistic contexts. This paper aims to enrich the understanding of these issues by exploring how strategy maps can be mobilized and used as boundary objects to elicit boundary-spanning practices that foster cross-boundary collaboration in pluralistic organizations.

This paper employs the case study methodology to capture the dynamics of cross-boundary management elicited by the use of a strategy map within a pluralistic social/healthcare organizational context.

This study identifies four practices of boundary spanning (i.e. identifying and crossing problem boundaries, orchestrating collective responsibilities, acknowledging a common understanding of convergent values and goals, and evolving into action) in the analysed pluralistic context and investigates the conditions under which cross-boundary interactions can mobilize a shared zone of knowing via strategy maps.

This paper suggests a complex (and not linear) processual model of boundary management in pluralistic contexts in which the use of the strategy map mobilizes a dynamic of centrifugal and centripetal movements which engage plural actors in a shared site of collaborative knowing. The study contributes to a conceptualization of boundary management in pluralistic contexts as a progressive social accomplishment.

This study, first, reviews the existing literature on electronic word-of-mouth (eWOM) and, using communication theory, examines its impact on its readers’ decision-making processes. Second, this paper aims to propose some elements of eWOM communications that might be further researched.

A literature review of relevant academic articles produced 97 works related to social communication theory, eWOM and new artificial intelligence trends in hospitality. Thereafter, potential avenues for future research were explored.

The study results showed: valence, relevance, understandability and visual cues are the most important antecedents of message usefulness and the reader’s behavioral intentions; source credibility is the sender characteristic that most affects the reader’s behavioral intentions and consumer susceptibility to interpersonal influence is the receiver characteristic that most influences their attitudes and behavioral intentions. In addition, the study highlights four relevant aspects for future research. First, more research into online fake reviews is needed to better understand sender motivations. Second, companies should actively manage negative reviews. Then, the careful choice of platforms on which companies promote their products/services. Finally, the role of artificial intelligence in increasing the effectiveness of eWOM in the hospitality industry.

This paper integrates – grounded on communication theory – results from previous studies about the central elements of communication (message, sender and receiver) and discusses the main trends in hospitality-related eWOM. In addition, the paper examines the potential of specific eWOM elements as future lines of research, in particular: fake reviews, strategies for dealing with negative reviews, the eWOM platform used and artificial intelligence applications.

Este estudio, en primer lugar, revisa la literatura existente sobre el boca-oído electrónico (eWOM) y, utilizando la teoría de la comunicación, examina su impacto en los procesos de toma de decisiones de sus lectores. En segundo lugar, proponemos algunos elementos de las comunicaciones eWOM que podrían investigarse más adelante.

Una revisión de la literatura de artículos académicos relevantes produjo 97 trabajos relacionados con la teoría de la comunicación social, eWOM y nuevas tendencias de inteligencia artificial en hotelería. A partir de entonces, se exploraron posibles vías de investigación futura.

Los resultados del estudio señalaron: 1) la valencia, la relevancia, la comprensibilidad y las señales visuales son los antecedentes más importantes de la utilidad del mensaje y las intenciones de comportamiento del lector; 2) La credibilidad de la fuente es la característica del emisor que más afecta las intenciones de comportamiento del lector; 3) La susceptibilidad del consumidor a la influencia interpersonal es la característica del receptor que más influye en sus actitudes e intenciones de comportamiento. Además, el estudio destaca cuatro aspectos relevantes para futuras investigaciones. Primero, se necesita más investigación sobre las reseñas falsas en línea para comprender mejor las motivaciones del emisor. En segundo lugar, las empresas deben gestionar activamente las críticas negativas. Luego, la cuidadosa elección de las plataformas en las que las empresas promocionan sus productos/servicios. Por último, el papel de la inteligencia artificial en el aumento de la eficacia de eWOM en la industria hotelera.

Este artículo integra –con base en la teoría de la comunicación– resultados de estudios previos sobre los elementos centrales de la comunicación (mensaje, emisor y receptor) y analiza las principales tendencias en eWOM relacionadas con la hostelería. Además, el artículo examina el potencial de elementos específicos de eWOM como líneas futuras de investigación, en particular: revisiones falsas, estrategias para lidiar con críticas negativas, la plataforma eWOM utilizada y aplicaciones de inteligencia artificial.

Palabras clave: eWOM, Teoría de comunicación, Revisiones falsas, Revisiones negativas, Inteligencia artificialTipo de artículo: Revisión de la literatura

本研究, 首先, 回顾了现有的关于电子口碑（eWOM）的文献, 并利用传播理论, 研究了它对读者决策过程的影响。其次, 我们提出了一些可能需要进一步研究的电子口碑传播的要素。

对相关学术文章的文献回顾产生了97篇与社会传播理论、eWOM和酒店业新的人工智能趋势有关的作品。此后, 对未来研究的潜在途径进行了探讨。

研究结果显示。1）价值、相关性、可理解性和视觉线索是信息有用性和读者行为意图的最重要的前因; 2）来源的可信度是最能影响读者行为意图的发送者特征; 3）消费者对人际影响的易感性是最能影响他们态度和行为意图的接受者特征。此外, 该研究还强调了未来研究的四个相关方面。首先, 需要对网上虚假评论进行更多的研究, 以更好地了解发送者的动机。其次, 公司应该积极管理负面评论。然后, 谨慎选择公司推广其产品/服务的平台。最后, 人工智能在提高酒店业eWOM的有效性方面的作用。

本文以传播理论为基础, 整合了以往关于传播中心要素（信息、发送者和接受者）的研究结果, 并讨论了与酒店业相关的电子WOM的主要趋势。此外, 本文还研究了特定的eWOM要素作为未来研究方向的潜力, 特别是：虚假评论、处理负面评论的策略、使用的eWOM平台和人工智能应用。

关键词：eWOM, 传播理论, 虚假评论, 负面评论, 人工智能。

Prediction is a critical task in targeted online advertising, where predictions better than random guessing can translate to real economic return. This study aims to use machine learning (ML) methods to identify individuals who respond well to certain linguistic styles/persuasion techniques based on Aristotle’s means of persuasion, rhetorical devices, cognitive theories and Cialdini’s principles, given their psychometric profile.

A total of 1,022 individuals took part in the survey; participants were asked to fill out the ten item personality measure questionnaire to capture personality traits and the dysfunctional attitude scale (DAS) to measure dysfunctional beliefs and cognitive vulnerabilities. ML classification models using participant profiling information as input were developed to predict the extent to which an individual was influenced by statements that contained different linguistic styles/persuasion techniques. Several ML algorithms were used including support vector machine, LightGBM and Auto-Sklearn to predict the effect of each technique given each individual’s profile (personality, belief system and demographic data).

The findings highlight the importance of incorporating emotion-based variables as model input in predicting the influence of textual statements with embedded persuasion techniques. Across all investigated models, the influence effect could be predicted with an accuracy ranging 53%–70%, indicating the importance of testing multiple ML algorithms in the development of a persuasive communication (PC) system. The classification ability of models was highest when predicting the response to statements using rhetorical devices and flattery persuasion techniques. Contrastingly, techniques such as authority or social proof were less predictable. Adding DAS scale features improved model performance, suggesting they may be important in modelling persuasion.

In this study, the survey was limited to English-speaking countries and largely Western society values. More work is needed to ascertain the efficacy of models for other populations, cultures and languages. Most PC efforts are targeted at groups such as users, clients, shoppers and voters with this study in the communication context of education – further research is required to explore the capability of predictive ML models in other contexts. Finally, long self-reported psychological questionnaires may not be suitable for real-world deployment and could be subject to bias, thus a simpler method needs to be devised to gather user profile data such as using a subset of the most predictive features.

The findings of this study indicate that leveraging richer profiling data in conjunction with ML approaches may assist in the development of enhanced persuasive systems. There are many applications such as online apps, digital advertising, recommendation systems, chatbots and e-commerce platforms which can benefit from integrating persuasion communication systems that tailor messaging to the individual – potentially translating into higher economic returns.

This study integrates sets of features that have heretofore not been used together in developing ML-based predictive models of PC. DAS scale data, which relate to dysfunctional beliefs and cognitive vulnerabilities, were assessed for their importance in identifying effective persuasion techniques. Additionally, the work compares a range of persuasion techniques that thus far have only been studied separately. This study also demonstrates the application of various ML methods in predicting the influence of linguistic styles/persuasion techniques within textual statements and show that a robust methodology comparing a range of ML algorithms is important in the discovery of a performant model.

Virtual assistants are increasingly used for persuasive purposes, employing the different modalities of voice and text (or a combination of the two). In this study, the authors compare the persuasiveness of voice-and text-based virtual assistants. The authors argue for perceived human-likeness and cognitive load as underlying mechanisms that can explain why voice- and text-based assistants differ in their persuasive potential by suppressing the activation of consumers' persuasion knowledge.

A pre-registered online-experiment (n = 450) implemented a text-based and two voice-based (with and without interaction history displayed in text) virtual assistants.

Findings show that, contrary to expectations, a text-based assistant is perceived as more human-like compared to a voice-based assistant (regardless of whether the interaction history is displayed), which in turn positively influences brand attitudes and purchase intention. The authors also find that voice as a communication modality can increase persuasion knowledge by being cognitively more demanding in comparison to text.

Simply using voice as a presumably human cue might not suffice to give virtual assistants a human-like appeal. For the development of virtual assistants, it might be beneficial to actively engage consumers to increase awareness of persuasion.

The current study adds to the emergent research stream considering virtual assistants in explicitly exploring modality differences between voice and text (and a combination of the two) and provides insights into the effects of persuasion coming from virtual assistants.

The purpose of this paper is to investigate the influence of entrepreneurs’ social competence (SC) on small and medium-sized enterprise (SME) performance.

Primary data of 250 manufacturing SMEs were collected through a survey method. The influence of SC on performance was tested using structural equation modelling (SEM).

Overall, the findings suggest that SC dimensions have a positive influence on SME performance in terms of nonfinancial perspective. More clearly, the findings show that out of five dimensions of SC, which include social adaptability, social perception, social expressiveness, persuasiveness and impression management; social perception, persuasiveness and impression management have direct effect on customer perspective; persuasiveness, social expressiveness and social adaptability have a direct influence on internal business processes and social adaptability, social perception, impression management and social expressiveness are directly related with learning and growth. Contrary to expectations though, social perception and social adaptability were significantly and negatively associated with internal business processes and customer perspective, respectively, while there was no significant correlation between social expressiveness, persuasiveness and impression management with customer perspective, business processes and learning and growth in that order.

The current study affirms that SMEs managed by entrepreneurs and managers who possess high levels of SC, may have a better performance compared to those operated by entrepreneurs with low levels of SC. This justifies a need for SME entrepreneurs and managers to work hard to improve their SC capabilities.

This study is pertinent and unique because, it extensively examines each of the five dimensions of SC in relation to nonfinancial indicators of SME performance. Besides, the study also provides additional evidence of the impact of SC on SME performance by suggesting that entrepreneurs who are socially competent are more likely to own highly successful ventures.

This paper aims to examine a two-way interaction between social influencers’ number of followers (micro vs meso) and argument quality (weak vs strong) on consumers’ self-reported and brain responses to advertising posts on Instagram. Further, drawing upon source credibility theory and contemporary theories of persuasion, the Instagram users’ perceptions of the influencer’s credibility are predicted to mediate the hypothesized effects.

Through an online (N = 192) and a lab study (N = 112), the authors examined Instagram users’ responses to an advertising post from Instagram influencers in terms of perceived source credibility and electronic word-of-mouth intention, using validated multi-item scales from existing literatures and electroencephalogram (EEG) measures. The hypotheses were tested with a 2 (type of influencer: micro vs meso) × 2 (argument quality: weak vs strong) between-subject design using mediated moderated linear regression analysis.

The results highlight that meso-influencers are perceived as a credible source of information only when their product-related post provides strong argument quality. Moreover, this process involves an increase in users’ cognitive work (measured with EEG), with possible implications on marketing communication strategies and online message design.

The limitations of the work can serve as ideas for future research. First, this study did not account for the influencer’s relevance and resonance. Second, the authors studied consumer responses to online communication produced by Instagram influencers within a single product category. Another important product type distinction that requires further attention is between hedonic and utilitarian products. Finally, the two studies only used positive review content. Further research should study how consumers evaluate the source credibility of a micro- vs meso-influencer when they are exposed to negative reviews containing weak vs strong arguments.

The results suggest that marketers should carefully consider Instagram influencers based on the trade-offs between credibility and reach. Specifically, micro-influencers are perceived as more credible sources of information than meso-influencers, which means that they have greater potential to affect Instagram users’ behavior. Moreover, the results suggest that meso-influencers should leverage argument quality to enhance their credibility and draw greater positive outcomes for the products and brands they endorse.

To the best of the authors’ knowledge, this study is the first to investigate how the interaction between the type of social media influencer and the argument quality affects consumers’ self-reported and brain responses to advertising posts on Instagram. Moreover, using neuroscience, this study aims to shed light on the neurophysiological processes that drive consumer responses to product-related communication posted by different influencer types.