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Conspicuously absent from the branding literature is research on the brand-to-brand (Br2Br) interface enabled by social media. The author proposes how networked brands-as-actors integrate their resources as Br2Br interactions that co-create consumer–brand value. As a secondary contribution, the author provides an empirical baseline exploration of the value co-creating impact of Br2Br interactions on consumer–brand evaluations and social media engagement.

Three streams of research aid in conceptualizing the value co-creating process of Br2Br interactions. A follow-up exploratory study uses a controlled Br2Br interaction stimulus in a 2 × 2 × 2 between-subjects design, where brand familiarity and product category complementarity are manipulated, and interaction spillover effects are analyzed using structural equation modeling.

The author finds Br2Br interactions positively affect consumer–brand evaluations and social media engagement likelihood. Spillover effects of these interactions are symmetric for consumer–brand evaluations for both brands. However, brand familiarity moderates the effects of Br2Br interactions on consumer–brand evaluations.

The author lays the groundwork for future research on the complexities of Br2Br interactions – including brand personality conflict, interaction duration and paratextual language – and the boundary conditions for Br2Br and brand-to-consumer relationships.

This theme issue aims to explore the depth and breadth of automation and artificial intelligence’s (AI’s) impact on the hospitality and tourism industry.

The thematic examination of the articles presented in this theme issue highlights the central results concerning the strategic inquiry, especially regarding their addition to knowledge, which is vital for fostering idea creation and theoretical research beneficial to various stakeholders in the tourism and hospitality sector. Given the swift evolution of these technologies, grasping their utilization, advantages and obstacles is essential for industry experts, decision-makers and scholars.

This theme issue encapsulates the transformative impact of automation and AI in the tourism and hospitality industry, highlighting the juxtaposition of enhanced operational efficiency against employment security concerns. It emphasizes the need for ethical governance to address AI’s ethical dilemmas and security vulnerabilities. The exploration of consumer attitudes towards AI, particularly in service robots and facial emotion recognition technologies, is deemed crucial for leveraging AI’s full potential in service delivery. Furthermore, AI’s entry into gastronomy prompts a reevaluation of traditional culinary practices, advocating for a balance between technological innovation and the preservation of cultural heritage.

This theme issue stands out for its focused exploration of the transformative effects of automation and AI within the hospitality and tourism industry. Unlike broader discussions on technology in business, it delves into specific AI-driven innovations, operational changes and the resultant shifts in consumer behavior and industry standards. By curating a collection of empirical research, theoretical analyses and content analyses, this issue is providing important insights into how automation and AI are reshaping service delivery, management practices and strategic decision-making in an industry characterized by its intense customer focus and reliance on human-to-human interaction.

The purpose of this study was to comprehend the adoption of artificial intelligence (AI) technology-driven natural large language model (LLM)-based chatbots by customers.

A qualitative research study method was conducted. This was to explore managerial perspectives towards consumer centric technology adoption of AI plus LLM-based chatbots. This was specifically for AI-driven natural LLM-based chatbots services. The author conducted conducted in-depth personal interviews with 32 experts of digital content AI + LLM chatbot services. Thematic content analysis was undertaken to analyse the data.

The advent of natural language processing tools driven by AI technology chatbots has altered human-firm interaction. The research findings indicated that the push-pull-mooring (PPM) factors captured the phenomenon in the most comprehensive way. A total of 15 key factors influencing the adoption of AI technology-driven natural LLM-based chatbots by customers during firm customer interaction were identified in this study by the author. The thematic content analysis unraveled insights regarding transformed consumer adoptions towards AI-driven LLM-based chatbots by means of the PPM framework factors.

The empirical research investigation contributed to the literature on the PPM theoretical framework. This was specifically in the context of adoption of AI technology-driven natural LLM-based chatbots by customers during firm customer interaction.

The research study insights would help managers to restructure and reconfigure their organizational processes. This would neccessiated a shift in firm-customer interactions as demanded because of the availability of AI technology-driven natural LLM-based chatbots by customers.

This research study was based upon the PPM theoretical framework. This study provided a unique analysis of the altered firm customer interaction needs and requirements. This was one of the first studies that applied the framework of PPM theory regarding the adoption of AI technology-driven natural LLM-based chatbots by customers.

Most previous studies predicting review helpfulness ignored the significance of deep features embedded in review text and instead relied on hand-crafted features. Hand-crafted and deep features have the advantages of high interpretability and predictive accuracy. This study aims to propose a novel review helpfulness prediction model that uses deep learning (DL) techniques to consider the complementarity between hand-crafted and deep features.

First, an advanced convolutional neural network was applied to extract deep features from unstructured review text. Second, this study used previous studies to extract hand-crafted features that impact the helpfulness of reviews and enhance their interpretability. Third, this study incorporated deep and hand-crafted features into a review helpfulness prediction model and evaluated its performance using the Yelp.com data set. To measure the performance of the proposed model, this study used 2,417,796 restaurant reviews.

Extensive experiments confirmed that the proposed methodology performs better than traditional machine learning methods. Moreover, this study confirms through an empirical analysis that combining hand-crafted and deep features demonstrates better prediction performance.

To the best of the authors’ knowledge, this is one of the first studies to apply DL techniques and use structured and unstructured data to predict review helpfulness in the restaurant context. In addition, an advanced feature-fusion method was adopted to better use the extracted feature information and identify the complementarity between features.

大多数先前预测评论有用性的研究忽视了嵌入在评论文本中的深层特征的重要性, 而主要依赖手工制作的特征。手工制作和深层特征具有高解释性和预测准确性的优势。本研究提出了一种新颖的评论有用性预测模型, 利用深度学习技术来考虑手工制作特征和深层特征之间的互补性。

首先, 采用先进的卷积神经网络从非结构化的评论文本中提取深层特征。其次, 本研究利用先前研究中提取的手工制作特征, 这些特征影响了评论的有用性并增强了其解释性。第三, 本研究将深层特征和手工制作特征结合到一个评论有用性预测模型中, 并使用Yelp.com数据集对其性能进行评估。为了衡量所提出模型的性能, 本研究使用了2,417,796条餐厅评论。

广泛的实验验证了所提出的方法优于传统的机器学习方法。此外, 通过实证分析, 本研究证实了结合手工制作和深层特征可以展现出更好的预测性能。

据我们所知, 这是首个在餐厅评论预测中应用深度学习技术, 并结合了结构化和非结构化数据来预测评论有用性的研究之一。此外, 本研究采用了先进的特征融合方法, 更好地利用了提取的特征信息, 并识别了特征之间的互补性。

The study aims to delve into the “phygital customer journey” (PCJ), which merges physical and digital interactions in customer experiences, using a practice-based lens to reveal the underlying dynamics of these blended encounters.

Feedback from 60 individuals established the groundwork for a qualitative analysis. They chronicled customer journeys through diaries and used UXPressia software for journey mapping. This strategy enabled a detailed exploration of the PCJ, focusing on customers’ lived experiences and perceptions.

The study presents an integrative framework for the PCJ, identifying four key elements: hybrid artefacts (the melding of digital and physical tools/interfaces), blended contexts (the seamless integration of digital and physical spaces), circular actions (the non-linear paths of customer engagement) and intertwined emotions (the complex emotional responses to phygital experiences). These elements underscore the intricate and interconnected nature of the PCJ.

This study advances the field by applying a practice-based approach to unravel the complexities of the PCJ, illuminating the nuanced interplay between digital and physical realms. This innovative lens foregrounds the significance of practices in consumer experiences, thereby contributing to a deeper academic and practical understanding of phygital integration.

The purpose of this study is to develop an integrated conceptual framework to better understand the psychological pathways connecting consumer perceptions to purchasing intentions for premium sustainable products.

The study develops a conceptual model that theorizes relationships between consumer perceptions of a firm’s innovation, competitive advantage, sustainable practices and stakeholder orientation. It proposes that stakeholder orientation mediates the effects of these perceptions on consumers’ willingness to purchase premium sustainable products. Additionally, lifestyle is hypothesized as a moderator. The model advances knowledge through eight testable propositions.

The conceptual framework specifies indirect, mediated and moderated relationships that have not been fully captured by past literature. It theorizes that perceptions of a firm’s innovation, competitive advantage from sustainable practices and stakeholder orientation indirectly influence purchase willingness through the mediating role of stakeholder orientation. Lifestyle is proposed to moderate these relationships.

This conceptual model offers insights for cultivating consumer perceptions that strengthen a firm’s stakeholder image and endorsement of premium sustainable products. Its validated theoretical lens and propositions can provide strategic guidance for addressing the challenges of higher price points for sustainable products through capturing psychological drivers of values-based decision-making. Future empirical assessment is recommended to validate the specified relationships in the model.

Two-sided messages in advertising, which contain both negative and positive information, can have varying effects on persuasion. Thus, it is crucial to understand the conditions under which such messages are more or less effective compared to one-sided messages that only contain positive information. This research investigates the moderating role of the visual angle (close-up vs. long shot) of an image by drawing upon construal level theory.

This research reports two experimental studies employing a 2 (message: two-sided [positive and negative information], one-sided [positive information as a control condition]) × 2 (visual angle: near [close-up], distant [long shot]) between-subjects design.

The results demonstrate that two-sided messages paired with a close-up image decrease positive electronic word of mouth (eWOM) due to increased feelings of ambivalence, while two-sided messages paired with a long-shot image increase positive eWOM due to increased perceived authenticity.

These findings provide insight into the impact of two-sided messages on advertising persuasion and provide guidance for marketers in developing effective communication strategies to leverage positive eWOM.

This paper aims to examine existing literature on halal food consumption from the perspective of consumer behaviour research. It identifies progress, current state and gaps and provides direction for future research to advance the field.

This paper reviewed papers from 2007 to 2023 using Scopus and WOS databases. The review used the Theories–Context–Characteristics–Methods (TCCM) framework and followed the scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR) protocol.

The review summarises the methods, theory and approaches used in the topic and presents key findings and a proposed framework. It can guide future researchers in developing their models, making it a valuable starting point for future research. Despite the existence of SRL in halal food to the best of the authors’ knowledge, this work is the first review that proposes a model for halal food in consumer behaviour.

This review provides a twofold contribution. First, this review's theoretical contribution is advancing consumer behaviour literature on halal food. Second, this work's practical contribution is to enrich practitioners' understanding of the antecedents of consumer behaviour regarding halal food. This is the first review proposing a consumer behaviour model for Halal food. It makes a theoretical contribution to understanding consumer behaviour on Halal food and provides practical insights for practitioners.

The social media communication of luxury service firms remains largely unexplored. This study explores the influence of firm-created social media communication (FCSMC) on predicting brand evangelism (BEM) via perceived values, including functional value (FV), emotional value (EV) and social value (SV), by embedding the direct and moderating influence of customer experience (CX) on brand evangelism in the luxury hotel sector.

This study recruited 405 regular travelers to participate in an online survey. Following meticulous data curation, the empirical analysis was performed on 363 responses using structural equation modeling.

The findings revealed that FCSMC substantially impacted perceived values, including FV, EV and SV, as well as BEM. Likewise, perceived values, including FV and EV, were positively associated with BEM. In addition, this study revealed that CX exhibited significant predictive capability with its direct and moderating effects on BEM in the luxury hotel sector.

This original research advances the uses and gratifications theory and attribution theory. It provides novel theoretical insights and practical recommendations for the luxury hotel sector.

The present study addresses the literature gap on cultural linkages, traditions, cultural recognition and the perceived benefits of consumers in the orange economy. The article focuses on analyzing the impact of traditions and cultural linkages on the relationship between cultural recognition and the perceived benefits of consumers.

The empirical study is conducted on a sample of 393 consumers from the city of Arequipa, Peru utilizing structural equation modeling (SEM) with Smart PLS software.

The research results demonstrate that traditions and cultural ties are important factors that entrepreneurs must consider in the production and marketing process to enhance the benefits perceived by consumers by providing cultural identity within the products.

The study provides theoretical implications that fill the existing gap in understanding the relationship between cultural recognition and perceived benefits. Additionally, it offers practical implications for the development of the cultural ecosystem, involving artisans, artists, cultural managers, entrepreneurs, businessmen, government authorities, non-governmental organizations and international organizations.