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This study aims to enhance the classification and processing of online appeals by employing a deep-learning-based method. This method is designed to meet the requirements for precise information categorization and decision support across various management departments.

This study leverages the ALBERT–TextCNN algorithm to determine the appropriate department for managing online appeals. ALBERT is selected for its advanced dynamic word representation capabilities, rooted in a multi-layer bidirectional transformer architecture and enriched text vector representation. TextCNN is integrated to facilitate the development of multi-label classification models.

Comparative experiments demonstrate the effectiveness of the proposed approach and its significant superiority over traditional classification methods in terms of accuracy.

The original contribution of this study lies in its utilization of the ALBERT–TextCNN algorithm for the classification of online appeals, resulting in a substantial improvement in accuracy. This research offers valuable insights for management departments, enabling enhanced understanding of public appeals and fostering more scientifically grounded and effective decision-making processes.

Although digital transformation (DT) has emerged as an important phenomenon for both research and practices, the influences remain inconclusive and inadequate. The emerging artificial intelligence (AI) technologies further complicate the understanding and practices of DT while understudied yet. To address these concerns, this study takes a process perspective to empirically investigate when and how digital-intelligence transformation can improve firm performance, aiming to enrich the literature on digital-intelligence transformation and strategic information systems (IS) field.

Drawing on the dynamic capability view and business agility, we took a process perspective to conceptualize and empirically examine the influence of digital-intelligence transformation and the process characteristics. Taking a continuous panel dataset of listed Chinese firms covering 2007 to 2020, we investigated digital-intelligence transformation’s effect on firm performance and the moderating roles of three strategic aspects: pace, scope and rhythm.

This study found that digital-intelligence transformation positively affects firm performance and is moderated by the characteristics of transformation processes (i.e. pace, scope and rhythm). Specifically, the high-paced and rhythmic transformation processes facilitate the positive relationship, while the large scope undermines the benefits of transformation. These relationships hold across various endogeneity and heterogeneity analyses.

Our findings provide valuable implications for digital-intelligence transformation and strategic IS field. First, this study enriches existing literature on digital-intelligence transformation by empirically investigating the influence from a process perspective. Moreover, this study provides insights into a comprehensive understanding of the complexity of digital-intelligence transformation and the influences of AI. Finally, this study provides practical implications on how to make digital-intelligence transformation to benefit firm performance.

This study aims to confirm the causal relationship between emotional brand attachment, brand love, and brand commitment, and then explain how these variables affect active engagement. In addition, it is to confirm the effect of brand prestige, brand consciousness, and brand trust on emotional brand attachment and to identify the moderating role of self-congruity in the causal relationship between these variables.

In this study, a survey was conducted targeting 320 consumers who have recently purchased luxury products or brands. In addition, structural equation model analysis (SEM) was used to test the research hypotheses raised in this study.

The results found that brand prestige and brand consciousness affect on emotional brand attachment. Emotional brand attachment had a significant effect on brand love and brand commitment. And brand love affect brand commitment and active engagement. Emotional brand attachment affects active engagement. Brand love was mediated in the relationship between emotional brand attachment and active engagement. Self-congruity was moderated in the relationship between brand prestige and emotional brand attachment. However, self-congruity was not moderated in the relation to brand consciousness, brand trust and emotional brand attachment.

This study has significance in that it identified the antecedent factors that cause consumers' emotional brand attachment and confirmed that they have differential effects depending on the degree of consumer self-congruity. In addition, this study is meaningful in that it confirmed the concept of the causal difference between attachment and brand love as consumers' emotional responses to luxury brands. However, the scope of this study was limited to offline stores excluding online purchases as a place of purchase for luxury brands. In a situation where the purchase of luxury brands is gradually increasing in various online environments, limiting the scope of the study to offline stores may have problems in generalizing the study. Therefore, in future research, we would like to propose a study on the relationship and influence between these variables by integrating all purchasing environments, such as offline and online.

The management implications of the results of this study are as follows. First, brand marketers and managers must suggest strategies to increase emotional attachment to customers who are satisfied with the brand and have a favorable brand attitude. After segmenting target customers and identifying their tendencies, behavioral characteristics, and preferred brands, emotional attachment can be strengthened by providing information about the brand to each segment and strengthening the brand image. Strategies like these can help target customers strengthen their emotional connection to a luxury brand, build positive attitudes toward the brand, and prevent them from switching to competing brands. Second, a strategy is needed to ensure that target customers have a strong emotional response to the company's luxury brand and become immersed in the brand. Target customers who have an affinity for the brand can strengthen their level of brand attachment and become immersed in the brand by allowing them to directly participate in brand activities through various advertising campaigns, events, and content. Third, you can strengthen your brand by developing a brand that fits the self-concept of your target customers. Brand marketers or managers can strengthen brand attachment by presenting a brand that fits the characteristics of each target customer and recognizing that the brand's status is relatively high compared to competing brands.

This study identified how consumers' brand engagement in a luxury brand environment is influenced by its components. In other words, the preceding factors for consumers' brand emotion were identified, and the influence of emotional brand attachment and brand love, which represent the consumer's emotional state that affects consumers' brand engagement, was investigated. The theoretical implications of the results of this study are as follows. First, Shahid et al. (2022) found that emotional attachment was expressed more strongly when emotional bonds were formed through relationship formation. Hwang and Kandampully (2012) found that emotional attachment and brand love are conceptually similar but differ in intensity. And Gómez-Suárez (2019) said that brand attachment is a prerequisite for brand love. As mentioned earlier, previous research has shown that emotional attachment and brand love differ depending on the consumer's emotional state. The results of this study showed that emotional brand attachment did not affect active participation, while brand love did. This means that active engagement is directly influenced by brand love rather than emotional attachment. Through these research results, it can be confirmed that even if consumers have similar brand emotional states, the impact on consumer behavior is different depending on the intensity of the emotional state. Therefore, in the consumer-brand relationship, the intensity of emotions arising from the interaction between the consumer and the brand is different, and only when brand emotions are at a high level, consumers engage in behavioral participation toward the brand. Second, Morris and Keltner (2000) found that consumers activate the integration of emotions in the decision-making process. Hwang and Kandampully (2012) found that love induces consumers to maintain a relationship with a brand, and that brand commitment increases when consumers feel intimacy and a strong emotional bond between themselves and the brand. Through these prior studies, it was confirmed that emotions play an important role in the consumer's decision-making process, and in particular, it was confirmed that maintaining close relationships with others induces emotional commitment to the object. In this study, brand loyalty was also found to have a positive effect on brand immersion and active participation. Therefore, consumers need to foster strong bonds with luxury brands to create brand love and strengthen their relationship with the brand, leading to brand commitment and active participation. Third, Ji et al. (2018) found that brand reputation has a positive effect on consumer attitudes and behaviors, including brand attachment, purchase intention, and brand loyalty. Casidy et al. (2015) found that consumers with high brand awareness are likely to have high brand preference and have favorable and positive brand attitudes due to their high brand knowledge. Previous research has shown that consumers' brand reputation and brand consciousness influence brand attachment.

This study dealt with a more comprehensive variable in the relationship between luxury brand factors as an antecedent variable of emotional brand attachment in luxury brand situations, and provided important evidence for the mediating effect of brand love, which was a limited emotional variable. In addition, additional implications for the moderating role of brand self-congruity on emotional brand attachment were suggested.

This study examined the role of brand experience (BE) dimensions (behavioural, intellectual, sensory and affective) to predict electronic word of mouth (e-WoM) through the mediating effect of brand love (BL) in the Egyptian organic cosmetics context.

In accordance with the non-probability convenience sampling procedure and through an online survey, the study collected 312 responses from female consumers who have used Egyptian organic cosmetics brands regularly within the past two years.

The findings revealed that BE has a significant direct positive effect on BL. BE has also had a significant direct positive effect on e-WoM. In addition, BL has a significant direct positive effect on e-WoM. Finally, BL is a significant mediator between BE and e-WoM.

This study offered several managerial recommendations. By considering BE as a tool, organic cosmetics' brand owners and managers can effectively develop and implement various experiential marketing strategies to create a love for that brand and develop long-term relationships with consumers, which in turn will lead to positive e-WOM.

This is a new study that uses Fournier’s relationship theory to investigate BE on BL to predict e-WOM in the context of Egyptian organic cosmetics brands. New insights are provided for the mediating effect of BL between BE and e-WoM in the context of Egyptian organic cosmetics brands.

Supply chains need to be made viable in this volatile and competitive market, which could be possible through digitalization. This study is an attempt to explore the role of Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business performance from the lens of natural resource-based view.

The study tests the proposed model using a covariance-based structural equation modelling and further investigates the ranking of each construct using the artificial neural networks approach in AMOS and SPSS respectively. A total of 234 respondents selected using purposive sampling aided in capturing the industry practices across supply chains in the UK. The full collinearity test was carried out to study the common method bias and the content validity was carried out using the item content validity index and scale content validity index. The convergent and discriminant validity of the constructs and mediation study was carried out in SPSS and AMOS V.23.

The results are overtly inferring the significant impact of Industry 4.0 practices on creating smart and ultimately sustainable supply chains. A partial relationship is established between Industry 4.0 and supply chain agility through a smart supply chain. This work empirically reinstates the combined significance of green practices, Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business value. The study also uses the ANN approach to determine the relative importance of each significant variable found in SEM analysis. ANN determines the ranking among the significant variables, i.e. supply chain resilience > green practices > Industry 4.0> smart supply chain > supply chain agility presented in descending order.

This study is a novel attempt to establish the role of digitalization in SCs for attaining sustainable business value, providing empirical support to the mediating role of supply chain agility, supply chain resilience and smart supply chain and manifests a significant integrated framework. This work reinforces the integrated model that combines all the constructs dealt with in silos so far in prior literature.

This paper aims to analyse the determinants of the intention to share a post about an environmental issue posted by a tourism destination on Facebook. The authors use the stimulus-organism-response (SOR) model as a theoretical framework and consider cognitive variables (destination social responsibility, tourist social responsibility and three types of congruence) as antecedents of emotions and of the tourists’ response (intention to share). Specific factors related to the social platform (attachment and active use of social media) are also included.

The model was tested for two destinations with different positioning (green tourism versus sun and beach). For the sampling strategy, the authors conducted an online poll targeting Facebook users who had undertaken at least one trip in the previous year. The sample consisted of 1,001 individuals.

The empirical evidence obtained indicates that consumer–cause congruence is the most important variable for explaining the intention to share the post for both destinations, with the destination–cause congruence being non-significant. The authors also observed that active participation on the social network stimulated the intention to share this specific content.

Unlike prior research, this paper examined consumer motivators for engaging with online corporate social responsibility content for tourism destinations, specifically focusing on destination social responsibility in sustainable tourism. The model also incorporates three types of congruence, revealing variations in their impact on explaining the intention to share sustainability-related posts.

This study aims to identify the most significant barriers and the stationary barrier to modular construction (MC) implementation and promote MC widespread use. By doing so, the construction industry can leverage the benefits of MC, such as faster construction times, improved quality control, reduced waste and increased sustainability.

This study uses a Gini’s mean analysis approach to identify the stationary barriers hindering the MC adoption in residential projects. The research focuses on the Egyptian context and uses a questionnaire survey to gather data from professionals in the construction industry.

According to the survey findings, the top five significant MC barriers are inability to modify the design; contractors asking for high bidding prices (higher initial cost); scepticism, conservation and resistance of clients to innovation and change; transportation restrictions; and lack of a one-size-fits-all tool for the design. In addition, Gini’s mean of dispersion demonstrated that the stationary barrier that faces MC adoption is the apprehension that architectural creativity will suffer because of MC.

The identified obstacles could be useful for decision makers in countries that have not yet adopted MC and may aid in the planning process to manage the risks associated with MC projects. The paper stresses the significance of devising techniques to overcome these barriers and proposes several methods to tackle these challenges.

This study fills the knowledge gap by identifying the stationary barrier and emphasising the potential risks associated with MC barriers. Furthermore, it suggests several strategies for overcoming and reducing these barriers in developing countries residential projects.

Male celebrities are increasingly being chosen to endorse female cosmetic brands by marketing managers, yet this practice has not received sufficient scholarly attention. This study aims to explore the dynamics of male celebrities endorsing cosmetic brands.

The study employs the netnography approach to collect data from an online community.

The study contributes to the marketing literature by providing a conceptual framework of male celebrities endorsing cosmetic brands, highlighting the key attributes that contribute to the effectiveness of these endorsements, the evolution of relationships between fans, celebrities and brands, the features of this dynamic relationship and the influence of male celebrity endorsements on fans’ purchase decisions.

This research sheds light on an emerging trend in the marketing industry and provides valuable managerial insights for marketers seeking to effectively use male celebrity endorsements to promote female cosmetic brands.

Video game streaming (VGS) is emerging as an extremely popular, highly interactive, inordinately subscribed and very dynamic form of digital media. Incorporated environmental elements, gratifications and user pre-existing attitudes in VGS, this paper presents the development of an extended model of uses and gratification theory (EUGT) for predicting users' behavior in novel technological context.

The proposed model was empirically tested in VGS context due to its popularity, interactivity and relevance. Data collected from 308 VGS users and structural equation modeling (SEM) was employed to assess the hypotheses. Multi-model comparison technique was used to assess the explanatory power of EUGT.

The findings confirmed three significant types elements in determining VGS viewers' engagement, including gratifications (e.g. involvement), environmental cues (e.g. medium appeal) and user predispositions (e.g. pre-existing attitudes). The results revealed that emerging technologies provide potential opportunities for new motives and gratifications, and highlighted the significant of pre-existing attitudes as a mediator in the gratification-uses link.

This study is one of its kind in tackling the criticism on UGT of considering media users too rational or active. The study achieved this objective by considering environmental impacts on user behavior which is largely ignored in recent UGT studies. Also, by incorporating users pre-existing attitudes into UGT framework, this study conceptualized and empirically verified the higher explanatory power of EUGT through a novel multi-modal approach in VGS. Compared to other rival models, EUGS provides a more robust explanation of users' behavior. The findings contribute to the literature of UGT, VGS and users' engagement.

In recent years patents have become a very popular data source for forecasting technological changes. However, since a vast amount of patents are “worthless” (Moore, 2005), there is a need to identify the promising ones. For this purpose, previous approaches have mainly used bibliographic data, thus neglecting the benefits of textual data, such as instant accessibility at patent disclosure. To leverage these benefits, this study aims to develop an approach that uses textual patent data for predicting promising patents.

For the identification of promising patents, the authors propose a novel approach which combines link prediction with textual patent data. Thereby the authors are able to predict the emergence of hitherto unmentioned bigrams. By mapping these future bigrams to recent patents, the authors are able to distinguish between promising and nonpromising patents. To validate this approach, the authors apply the methodology to the case example of camera technology.

The authors identify stochastic gradient descent as a suitable algorithm with both a receiver operating characteristic area under curve score and a positive predictive value of 78%, which outperforms chance by a factor of two. In addition, the authors present promising camera patents for diverse application fields, such as cameras for surgical systems, cameras for rearview vision systems in vehicles or light amplification by stimulated emission of radiation detection and ranging cameras for three-dimensional imaging.

This study contributes in at least three directions to scholarship. First, the authors introduce a novel approach by combining link prediction with textual patent analysis and, in this way, leverage the benefits of both worlds. Second, the authors add to all theories that regard novel technologies as a recombination of existing technologies in presenting word combinations from textual data as a suitable instrument for revealing recombination in patents. And third, the approach can be used by scholars as a complementary or even integrative tool with conventional forecasting methods like the Delphi technique or Scenario planning.

At least three practical implications arise from the study. First, incumbent firms of a technology branch can use this approach as an early-warning system to identify technological change and to identify opportunities related to their company’s technological competence and provide inspiration for new ideas. Second, companies seeking to tap into new markets may also be interested in the approach as managers could anticipate whether their company’s technological competences are in line with upcoming trends. Third, the approach may be used as a supportive tool for various purposes, such as investment decisions or technology life cycle analysis.

The approach introduces textual patent data as suitable means for forecasting activities. As the statistical validation reveals, the promising patents identified by the approach are cited significantly more often than patents with less promising prospects.