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The authors investigate the varying impact of three categories of conflicting consumer reviews (i.e. conflicting opinions on attributes of a product item, conflicting ratings of an item and the intensity of conflicting reviews of an item) on the potential customers' perceived informativeness, which is expected to affect the perceived correct purchase.

To test their proposed hypotheses, the authors conducted an experiment using a 2 × 2 × 2 factorial design for each conflict type comprising two levels (low vs high).

The results of this study found that conflicting opinions on product attributes can enhance potential customers' perceptions of informativeness and subsequent correct purchase decisions while conflicting ratings and the intensity of conflicting reviews can diminish potential customers' perceptions of informativeness. In addition, conflicting ratings negatively moderate the effect of conflicting attributes on perceived informativeness such that the positive effect of conflicting attributes on perceived informativeness will be less prominent when conflicting ratings are present (vs absent).

While potential customers are browsing product descriptions, reviews and comments from other purchasers are also playing a role in influencing a potential customer's purchase decision. However, given the different experiences and temperaments of individuals, the subjective remarks and ratings of individuals are sometimes inconsistent or even conflicting, which can lead to confusion among potential customers. The authors categorize the positive or negative effects of the three conflicting reviews based on the two dimensions of ease of capture and product diagnosticity. The findings can help platforms optimize the display of product reviews to help potential customers make more accurate purchase decisions.

The purpose of this paper is to offer a comprehensive overview of current research on customer behavior in the business-to-business (B2B) context and propose a research agenda for future studies. Despite being a relatively recent area of interest for academics and practitioners, a literature review that synthesizes existing knowledge into coherent topics and outlines a research agenda for future research is still lacking.

Drawing on a systematic literature review of 219 papers and using a text-mining approach based on the Latent Dirichlet Allocation algorithm, this paper enhances the existing knowledge of B2B customer behavior and provides a descriptive analysis of the literature.

From this review, ten major research topics are found and analyzed. These topics were analyzed through the lens of the Theory, Context, Characteristics and Method framework, providing a summary of key findings from prior studies. Additionally, an integrative framework was developed, offering insights into future research directions.

This study presents a novel contribution to the field of B2B by providing a systematic review of the topic of customer behavior, filling a gap in the literature and offering a valuable resource for scholars and managers seeking to advance the field.

The main goal of this paper is to identify the attributes of consumer experience in Michelin-starred restaurants and to estimate their effects on restaurant ratings.

A sample of 70,233 online reviews of 224 Spanish Michelin-starred restaurants were analysed with the latent Dirichlet allocation algorithm. A sentiment analysis and a logistic regression analysis were also employed to estimate the effect of attributes on restaurant ratings.

Customer attention, food quality, decor and ambience and value for money are frequently used to define restaurant experience. However, it is shown in this study that the experience in a Michelin-starred restaurant goes beyond the evaluation of those four attributes. Furthermore, the effect of the factors that were identified on customer satisfaction differed depending on the restaurant ratings.

The findings are linked to the context of Spanish Michelin-starred restaurants. It is also assumed in this study that online reviews are based on truthful opinions.

Restaurant managers should primarily focus on customer attention and food quality to achieve customer satisfaction. In addition, those restaurants with an error-free service and a highly appreciated wine list among diners are more likely to achieve the culinary excellence that deserves a 5-star rating on TripAdvisor.

The attributes of the restaurant experience are frequently identified in literature reviews. Research based on text-mining analyses of customer reviews to discover a posteriori the factors that define a restaurant experience is scarce, and particularly difficult to find in the context of Michelin-starred restaurants.

Engaging in webcare, i.e. responding to online reviews, can positively affect consumer attitudes, intentions and behavior. Research is often scarce or inconsistent regarding the effects of specific webcare strategies on business performance. Therefore, this study tests whether and how several webcare strategies affect hotel bookings.

We apply machine learning classifiers to secondary data (webcare messages) to classify webcare variables to be included in a regression analysis looking at the effect of these strategies on hotel bookings while controlling for possible confounds such as seasonality and hotel-specific effects.

The strategies that have a positive effect on bookings are directing reviewers to a private channel, being defensive, offering compensation and having managers sign the response. Webcare strategies to be avoided are apologies, merely asking for more information, inviting customers for another visit and adding informal non-verbal cues. Strategies that do not appear to affect future bookings are expressing gratitude, personalizing and having staff members (rather than managers) sign webcare.

These findings help managers optimize their webcare strategy for better business results and develop automated webcare.

We look into several commonly used and studied webcare strategies that affect actual business outcomes, being that most previous research studies are experimental or look into a very limited set of strategies.

Effective customer journey design (ECJD) is considered a key variable in customer experience management and an essential source of brand meaning and pro-brand behavior. Although previous research has confirmed its importance for driving brand attitudes and loyalty, the role of consumer-brand identification as a social identity-based influence in this relationship has not yet been discussed. Drawing on construal level and social identity theories, this paper aims to investigate whether effective journeys and the resulting overall journey experience are equally powerful in driving brand loyalty among customers with different levels of consumer-brand identification.

The present article develops and tests a research model using data from the European and US service sectors (N = 1,454) to investigate how and when ECJD affects service brand loyalty.

Across two cultural contexts, four service industries and 33 service brands, the results reveal that ECJD is a crucial driver of service brand loyalty for customers with low consumer-brand identification. Moreover, the findings show that different aspects of journey effectiveness positively impact the valence of customers’ experience related to those journeys – a process that is ultimately decisive for their brand loyalty.

This study is unique because it generates theoretical and practical knowledge by combining the literature streams of customer journey design, customer experience and branding. Furthermore, this work demonstrates that consumer-brand identification is a critical boundary condition to be considered in the relationship between ECJD and brand loyalty in services.

The aim of this work is to provide a theoretical model that can help companies to develop a unique approach to achieve both corporate environmental sustainability (CES) and successful customer experience management (CEM).

A two-phase study achieved the research aim. The first phase consisted of the analysis of contemporary theoretical contributions with a focus on CES and CEM. In the second phase, taking a qualitative approach, the key dimensions identified in the initial analysis were investigated to explore the dominant perceptions of practitioners and to hone the theoretical categories.

Five innovative pathways emerged from the study to inform decision-making while maintaining the dual objectives of CES and successful CEM. These pathways are combined to offer a strategic tool for managers and for research advances. This original integrated model also offers six novel theoretical propositions that describe how to shape corporate decisions to achieve environmental sustainability in CEM.

Firms can benefit from an approach that integrates CES and CEM to develop a new mindset for an innovative and valuable decision-making process and to design more captivating experiences for customers. Nevertheless, the efficacy and generalizability of the theoretical framework and propositions require empirical testing.

This paper makes an original contribution to the environmental sustainability and marketing literature by bringing together all elements in these fields of research in a conceptual model. Moreover, this paper proposes theoretical propositions that advance knowledge of the subject and offer ideas for future research and managers.

This paper aims to address three research questions (1) Who is the main stakeholder that shapes Airbnb experience, (2) Does Airbnb offers an authentic travel experience? and (3) What should be the future research trends in Airbnb?

This paper uses the systematic literature review (SLR) with a well-defined protocol, research strategy and methods to answer the research questions.

The review revealed that while Airbnb plays a significant role as the platform provider, the stakeholders influencing the experiences are multifaceted. Hosts, guests, local communities and even regulatory bodies all contribute to shaping the overall Airbnb Experience ecosystem. Hosts, in particular, have a crucial role in curating and delivering unique experiences, which significantly impacts the quality and authenticity of the offerings. On the question of whether Airbnb offers an authentic travel experience, the review uncovered mixed findings. For examples, some studies emphasized the potential for Airbnb to provide authentic and local experiences, allowing travelers to engage with the community and cultural aspects of a destination. However, other studies raised concerns about the commodification and standardization of experiences, leading to a potential loss of authenticity.

This paper is different from previous SLR where previous research systematically reviewed; motivations to use and choose Airbnb, institutionalization of Airbnb, stakeholders of Airbnb. This paper addresses authentic experience as a factor that influences activity participation.

This study, grounded in the SOR theory, aims to enrich the understanding of customer citizenship behaviour in omnichannel fashion retail by examining how different customer experiences enhance customer engagement and how that engagement leads to customer citizenship behaviour. The influence of return policies on the relationship between customer engagement and customer citizenship behaviour was also examined.

Partial least squares structural equation modelling (PLS-SEM) is used to examine the framework of the proposed study with data collected through a survey (n = 251) to examine the opinions of the respondents about the variables mentioned. The authors also assessed the proposed framework using predictive power assessment using PLS predict.

The study results reveal that customers’ experiences of integration and flexibility in omnichannel retail are positively associated with their engagement. However, customer experiences of connectivity, consistency and personalization do not appear to affect customer engagement significantly in omnichannel retail. The return policy positively moderates the relationship between customer engagement and customer citizenship behaviour in the omnichannel fashion retail context. Predictive power assessment shows that the proposed model has high prediction accuracy.

This study contributes to the marketing literature by investigating different dimensions of consumer experience collectively and its impact on customer engagement and citizenship behaviour. Furthermore, the study contributes to omnichannel retail in fashion industry by testing the return policy as a moderator variable on the relationship between customer engagement and citizenship behaviour.

Este estudio, basado en la teoría SOR, enriquece la comprensión del comportamiento cívico del cliente en el comercio minorista de moda omnicanal examinando cómo las diferentes experiencias del cliente mejoran el compromiso de éste y cómo dicho compromiso conduce al comportamiento cívico del cliente. También se examina la influencia de las políticas de devolución en la relación entre el compromiso del cliente y el comportamiento ciudadano del cliente.

Se utilizó la modelización PLS-SEM para examinar el marco del estudio propuesto con datos recogidos mediante una encuesta (n = 251) para examinar las opiniones de los encuestados sobre las variables mencionadas. Los autores también evaluaron el marco propuesto mediante una evaluación del poder predictivo utilizando la predicción PLS.

Los resultados revelan que las experiencias de integración y flexibilidad de los clientes en el comercio minorista omnicanal se asocian positivamente con su compromiso. Sin embargo, las experiencias de los clientes de conectividad, coherencia y personalización no parecen afectar significativamente al compromiso del cliente en el comercio minorista omnicanal. La política de devoluciones modera positivamente la relación entre el compromiso del cliente y el comportamiento ciudadano en el contexto del comercio minorista de moda omnicanal. La evaluación del poder predictivo mostró que el modelo propuesto tenía una alta precisión de predicción.

El estudio contribuye a la literatura de marketing investigando colectivamente diferentes dimensiones de la experiencia del consumidor y su impacto en el compromiso del cliente y el comportamiento ciudadano. Además, este estudio contribuye a la venta minorista omnicanal en la industria de la moda al probar la política de devoluciones como variable moderadora de la relación entre el compromiso del cliente y el comportamiento ciudadano.

本研究以 SOR 理论为基础, 通过研究不同的顾客体验如何提高顾客参与度, 以及顾客参与度如何推动顾客公民行为, 丰富了对全渠道时尚零售中顾客公民行为的理解。研究还探讨了退货政策对顾客参与和顾客公民行为之间关系的影响。

本文采用 PLS-SEM 模型来检验拟议的研究框架, 并通过调查（n = 251）收集数据, 以检验受访者对上述变量的看法。作者还通过使用 PLS 预测评估预测能力, 对提出的框架进行了评估。

通过调查（n = 251）收集的数据, 使用 PLS-SEM 模型来研究拟议的研究框架, 以考察受访者对上述变量的看法。作者还通过使用 PLS 预测评估预测能力, 对提出的框架进行了评估。

研究结果表明, 顾客在全渠道零售中对整合性和灵活性的体验与他们的参与度呈正相关。然而, 顾客在连通性、一致性和个性化方面的体验似乎并未对顾客参与全渠道零售产生显著影响。退货政策对全渠道时尚零售中顾客参与和公民行为之间的关系起到了积极的调节作用。 预测能力评估表明, 所提出的模型具有较高的预测准确性。

本研究通过对消费者体验的不同维度及其对顾客参与和公民行为的影响进行综合研究, 为营销文献做出了贡献。此外, 本研究通过检验退货政策作为顾客参与和公民行为之间关系的调节变量, 为时尚行业的全渠道零售做出了贡献。

Since the outbreak of the Covid-19 pandemic, many restaurants and catering businesses have introduced or improved online food ordering and delivery services (OFODSs). This study aims to identify service quality expectations about OFODSs, to examine their content and to suggest management strategies to meet these expectations.

Adopting a qualitative method, four focus groups were conducted amongst Italian users of OFODSs.

The results reveal three dimensions of expectations, each comprising two categories that can be set along a continuum: (1) basicness of expectations (ranging from implicit to explicit), (2) accuracy of expectations (ranging from fuzzy to precise) and (3) attainability of expectations (ranging from realistic to unrealistic). Content may refer to technical, social, economic, legal and technological aspects. To meet customer expectations, the following strategies are suggested: customer reassurance, flexibility, continuous improvement, customer education, adaptation to customers' requirements and monitoring of exceptions.

This study provides specific activities in which restaurants and catering businesses could invest to enact the management strategies that emerged from the analysis.

This paper proposes a new classification of expectations and framework for improving OFODS quality by managing customer expectations.

The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.