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We explore the relationship between urbanicity and police officers’ perceptions of changes in their reactive and proactive work during the COVID-19 pandemic.

Using the 2021 survey of 1,262 Croatian police offices (436 police officers from a large urban community, 471 police officers from small towns and 155 from rural communities), we examine the perceived changes in their reactive activities (e.g. responses to the calls for service, arrests for minor crimes) and proactive activities (e.g. community policing activities, directed patrols) during the peak month of the pandemic compared to before the pandemic.

The majority of police officers in the study, regardless of the size of the community where they lived, reported no changes before and during the pandemic in reactive and proactive activities. Police officers from urban communities and small towns were more likely to note an increase in domestic violence calls for service. Police officers from urban communities were also more likely than the respondents from small towns and rural communities to report an increase in the responses to the disturbances of public order. Finally, police officers from small communities were most likely to observe a change in the frequency of traffic stops during the pandemic.

This study is the first one to explore the differences in perceptions of COVID-19-related changes in reactive and proactive police activities in a centralized police system.

The business ambiguity because of COVID-19 has brought the tourism industry under stress. Using the service-dominant-logic and elaboration-likelihood-model, this study tested the effects of destination-based cognitive, affective and behavioral customer brand engagement (CBE) on customer brand co-creation (CBC). This research also examined the effects of involvement and CBC on customer revisit intention (CRI) during the COVID-19 pandemic. This study also tested the moderating role of customers’ age among the modeled relationships.

Investigating these matters, a sample of 315 tourists was recruited and adopted a mixed-method approach, including structural equation modeling (SEM) as well as fuzzy set qualitative-comparative analysis (fsQCA).

SEM results render that CBE’s dimensions exercise different impacts on CBC, which affect revisit-intention. Results ascertain customer involvement’s direct effects on CBC and revisit intention. Multi-group analysis uncovers that consumer age significantly moderates the CBC and CRI relationship, and their effect increases as consumers get older. The fsQCA results revealed more heterogenous combinations to predict CBC and revisit intention.

This study focuses on CBE, CBC and involvement, and contributes unique insight to tourism marketing research; thus, it identifies plentiful opportunities for further research, as summarized.

This study offers key implications for destinations to build tourism/marketing strategies to strengthen the CBE/CBC or tourist/destination–brand relationship.

Though CBE/CBC and involvement are identified as important research priorities, empirically derived insights among these and related factors remain limited in the course of the COVID-19 crisis.

本文采用结构方程模型(SEM)和模糊集定性比较分析(fsQCA)相结合的方法, 对315名游客进行了调查。

由于新型冠状病毒感染症(COVID-19)产生的业务不定性给旅游业带来了压力。本研究运用服务主导逻辑和精细似然模型, 检验了基于目的地的认知、情感和行为顾客品牌参与(CBE)对顾客品牌共同创造(CBC)的影响。本研究还考察了COVID-19大流行期间参与和CBC对客户重访意愿(CRI)的影响。检验了顾客年龄在模型关系中的调节作用。

SEM结果表明, CBE的维度对CBC有不同的影响, 而这种影响又会影响着重游意愿。结果确定了游客参与对CBC和重访意愿的直接影响。多群体分析发现, 消费者年龄显著调节CBC和CRI关系, 且随着消费者年龄的增长, 其作用增强。fsQCA结果显示需更多的异质组合来预测CBC和再访意向。

-本研究关注CBE、CBC和参与, 为旅游营销研究提供了独特的见解, 因此总结出了许多进一步研究的机会。

本研究为目的地建立旅游/营销策略以加强CBE/CBC或游客/目的地-品牌关系提供了重要启示。

尽管CBE/CBC和参与被认为重要的研究重点, 但在covid −19危机期间, 从这些因素和相关因素中得出的经验见解仍然有限。

Para investigar estas cuestiones, se seleccionó una muestra de 315 turistas y se utilizó un enfoque metodológico mixto que incluía el modelo de ecuaciones estructurales (SEM) y el análisis cualitativo-comparativo de conjuntos difusos (fsQCA).

La confusión empresarial debida a la pandemia del COVID-19 ha sometido al sector turístico a una fuerte tensión. Utilizando la lógica dominante del servicio y el modelo de elaboración de verosimilitud, este estudio examinó los efectos del compromiso cognitivo, afectivo y comportamental del cliente con la marca del destino (CBE) en la cocreación de la marca (CBC). Esta investigación también analizó los efectos de la implicación y la CBC en la intención de revisita (IRC) durante la pandemia COVID-19. Este estudio también evaluó el papel moderador de la edad de los clientes entre las relaciones establecidas.

Los resultados del SEM muestran que las dimensiones de la CBE ejercen diferentes impactos sobre la CBC, que afectan a la intención de revisita. Los resultados determinan los efectos directos de la implicación del cliente sobre la CBC y la intención de revisita. El análisis multigrupo revela que la edad del consumidor modera significativamente la relación entre el CBC y el IRC, y que su efecto aumenta a medida que los consumidores envejecen. Los resultados del fsQCA revelaron combinaciones más heterogéneas para predecir el CBC y la intención de volver a visitar.

Este estudio se centra en la CBE, la CBC y la implicación, y aporta una visión única a la investigación del marketing turístico, por lo que identifica numerosas oportunidades para futuras investigaciones.

Este estudio ofrece implicaciones clave para que los destinos construyan estrategias de turismo/marketing en el fortalecimiento de la relación CBE/CBC o turista/destino-marca.

Aunque la CBE/CBC y la implicación se identifican como importantes prioridades de investigación, las percepciones derivadas empíricamente entre estos factores y otros relacionados siguen siendo limitadas en el transcurso de la crisis del COVID-19.

The purpose of this study is to comprehend how AI aids marketers in engaging customers and generating value for the company by way of customer engagement (CE). CE is a popular area of research for scholars and practitioners. One area of research that could have far-reaching ramifications with regard to strengthening CE is artificial intelligence (AI). Consequently, it becomes extremely important to understand how AI is helping the marketer reach customers and create value for the firm via CE.

A detailed approach using both systematic review and bibliometric analysis was used. It involved identifying key research areas, the most influential authors, studies, journals, countries and organisations. Then, a comprehensive analysis of 50 papers was carried out in the four identified clusters through co-citation analysis. Furthermore, a content analysis of 42 articles for the past six years was also conducted.

Emerging themes explored through cluster analysis are CE concepts and value creation, social media strategies, big data innovation and significance of AI in tertiary industry. Identified themes for content analysis are CE conceptualisation, CE behaviour in social media, CE role in value co-creation and CE via AI.

CE has emerged as a topic of great interest for marketers in recent years. With the rapid growth of digital media and the spread of social media, firms are now embarking on new online strategies to promote CE (Javornik and Mandelli, 2012). In this review, the authors have thoroughly assessed multiple facets of prior research papers focused on the utilisation of AI in the context of CE. The existing research papers highlighted that AI-powered chatbots and virtual assistants offer real-time interaction capabilities, swiftly addressing inquiries, delivering assistance and navigating customers through their experiences (Cheng and Jiang, 2022; Naqvi et al., 2023). This rapid and responsive engagement serves to enrich the customer’s overall interaction with the business. Consequently, this research can contribute to a comprehensive knowledge of how AI is assisting marketers to reach customers and create value for the firm via CE. This study also sheds light on both the attitudinal and behavioural aspects of CE on social media. While existing CE literature highlights the motivating factors driving engagement, the study underscores the significance of behavioural engagement in enhancing firm performance. It emphasises the need for researchers to understand the intricate dynamics of engagement in the context of hedonic products compared to utilitarian ones (Wongkitrungrueng and Assarut, 2020). CEs on social media assist firms in using their customers as advocates and value co-creators (Prahalad and Ramaswamy, 2004; Sawhney et al., 2005). A few of the CE themes are conceptual in nature; hence, there is an opportunity for scholarly research in CE to examine the ways in which AI-driven platforms can effectively gather customer insights. As per the prior relationship marketing studies, it is evident that building relationships reduces customer uncertainty (Barari et al., 2020). Therefore, by using data analysis, businesses can extract valuable insights into customer preferences and behaviour, equipping them to engage with customers more effectively.

The rapid growth of social media has enabled individuals to articulate their thoughts, opinions and emotions related to a brand, which creates a large amount of data for VCC. Meanwhile, AI has emerged as a radical way of providing value content to users. It expands on a broader concept of how software and algorithms work like human beings. Data collected from customer interactions are a major prerequisite for efficiently using AI for enhancing CE. AI not only reduces error rates but, at the same time, helps human beings in decision-making during complex situations. Owing to built-in algorithms that analyse large amounts of data, companies can inspect areas that require improvement in real time. Time and resources can also be saved by automating tasks contingent on customer responses and insights. AI enables the analysis of customer data to create highly personalised experiences. It can also forecast customer behaviour and trends, helping businesses anticipate needs and preferences. This enables proactive CE strategies, such as targeted offers or timely outreach. Furthermore, AI tools can analyse customer feedback and sentiment across various channels. This feedback can be used to make necessary improvements and address concerns promptly, ultimately fostering stronger customer relationships. AI can facilitate seamless engagement across multiple digital channels, ensuring that customers can interact with a brand through their preferred means, be it social media, email, or chat. Consequently, this research proposes that practitioners and companies can use analysis performed by AI-enabled systems on CEB, which can assist companies in exploring the extent to which each product influences CE. Understanding the importance of these attributes would assist companies in developing more memorable CE features.

This study examines how prominent CE and AI are in academic research on social media by identifying research gaps and future developments. This research provides an overview of CE research and will assist academicians, regulators and policymakers in identifying the important topics that require investigation.

In banking services, how customers interact with their bank – whether it’s through the physical branch or online – plays a significant role in how they feel about the experience. It’s not just about performing the service; it’s also about building trust, keeping them committed and getting them engaged so that a long-lasting relationship is developed. While there’s abundant research about trust and commitment in banking, not many studies have looked at how customers see both the online and offline sides of banking, especially in credit unions. Credit unions emphasize proximity with members, so it’s important to understand how these different ways of interacting affect how much people trust the credit union and stay committed to it and how engaged they feel as members. This study aims to explore this issue.

A quantitative survey was conducted using partial least squares structural equation modeling (PLS-SEM). The survey was answered by 195 members of one of the most traditional credit unions in Brazil.

The results suggest that both face-to-face and digital channels’ dimensions impact trust, which in turn influences commitment. Engagement is influenced by both trust and commitment, providing inputs to the value co-creation process.

The research presents relevant contributions to academia by deepening the understanding of the role of different service channels in value co-creation and customer engagement. It also offers significant contributions to the cooperative, which can improve the member experience in interaction channels to consequently develop lasting relationships and stimulate the engagement of its members.