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Building on the relationship marketing and stimulus-organism-response (SOR) theory, the purpose of this paper is to study the impact of the integrated store service quality (ISSQ) on the omnichannel customer lifetime value (CLV). The mediating role of customer commitment (affective, normative and continuance) and relationship program receptiveness with the moderating role of customer relationship proneness were relied upon to better understand the omnichannel customer profitability metric (CLV).

The study is descriptive and relies upon the cross-sectional data collected using the self-administered structured questionnaires from 785 omnichannel shoppers. A purposive sampling technique was performed in the study. Structural equation modeling was performed using the SMART-PLS 4.0 software to analyze the data.

The results indicate that omnichannel customer commitment (affective, normative and continuance) differentially mediates the relationship between ISSQ and relationship program receptiveness, subsequently impacting the omnichannel CLV. The customer relationship proneness significantly and positively moderated the relationships between different dimensions of customer commitment and relationship program receptiveness.

The study relied upon the cross-sectional data from the Indian population aged above 18 years for testing the proposed model. Further studies could test the model across different populations to generalize the study results.

This study addresses the need to investigate the omnichannel retail store customer profitability and their relationship performance with the store. By testing the customer relationship management model in the omnichannel retail store context, this study is the first to show that ISSQ will impact the customer profitability and relationship performance metric (CLV) through omnichannel customer commitment and relationship program receptiveness. The moderating effect of customer relationship proneness on a few proposed hypotheses was also tested to give managerial recommendations.

This study examines factors that affect customer lifetime value (CLV) in fast-food restaurants (FFRs) in Jordan. These factors are relational benefits, brand experiences, service quality (SQ), satisfaction, trust and commitment.

An online survey was collected from a sample of 503 respondents. The authors used SPSS to test the constructs' relationships and analyse the data. SmartPLS was used to test the hypotheses.

In contrast to previous studies, not all dimensions of brand experiences and relational benefits had a significant and positive influence on relationship marketing outcomes (satisfaction, trust and commitment). On the other hand, results demonstrated that SQ had a significant and positive influence on relationship marketing outcomes. Furthermore, research reveals that satisfaction, trust and commitment significantly and positively influenced CLV.

Those FFRs that seek to enhance CLV should build solid and sustainable bonds with their customers. This paper concludes by stating its implications, its limitations and the opportunities available for future research.

This study, which is unique in the Middle East, includes essential strategies for managing customer relationship that can be universally applied to improve customer benefits and maximise the performance of businesses.

This study aims to capture how the association between a multichannel relational communication strategy (MRCS) and customer performance is contingent upon such customer performance (low- versus high-performance customers) and to reconcile past contradictory results in this marketing-related topic. To this end, the authors propose and validate the method of quantile regression as an unconventional, yet effective, means to proceed to that reconciliation.

This study collected data from 4,934 customers of a private pension fund firm and accounted for both firm- and customer-initiated relational communication channels (RCCs) and for customer lifetime value (CLV). This study estimated a generalized linear model and then a quantile regression model was used to account for customer performance heterogeneity.

This study finds that specific RCCs present different levels of association with performance for low- versus high-performance customers, where outcome customer performance is the dependent variable. For example, the relation between firm-initiated communication (FIC) and performance is stronger for low-CLV customers, whereas the relation between customer-initiated communication (CIC) and performance is increasingly stronger for high-CLV customers but not for low-CLV ones. This study also finds that combining different forms of FIC can result in a negative association with customer performance, especially for low-CLV customers.

The authors tested the conceptual model in one single firm in the specific context of financial services and with cross-sectional data, so there should be caution when extrapolating this study’s findings.

This study offers nuanced and precise managerial insights on recommended resource allocation along with relational communication efforts, showing how managers can benefit from adopting a differentiated-customer performance approach when designing their MRCS.

This study provides an overview of the state of the art of MRCS, proposes a contingency analysis of the relationship between MRCS and performance based on customer performance heterogeneity and suggests the quantile method to perform such analysis and help reconcile past contradictory findings. This study shows how the association between RCCs and CLV varies across the conditional quantiles of the distribution of customer performance. This study also addresses a recent call for a more holistic perspective on the relationships between independent and dependent variables.

There is an ongoing challenge to map the efficacy of e-retailing strategies in building both value co-creation opportunities for online customers and customer value for companies. Based on the service-dominant (S-D) logic, an integrative model is provided that connects the impact of convenience and personalisation strategies (CPSs) on an e-retailer's performance – by offering co-creation opportunities and customer engagement.

The survey instrument is validated and the model is tested with data from active online customers using a novel methodology that blends artificial neural network (ANN) analysis with partial least squares (PLS) in both the measurement model and the path analysis.

The findings robustly support the model and yield evidence of the contribution of CPSs in effective value propositions, the interface between the S-D logic and customer engagement, and the direct effect of customer engagement on tangible forms of value for companies.

This study is the first scholarly effort to provide a comprehensive understanding of how and why CPSs can maximise customer value for the e-retailer, while simultaneously testing the customer value/engagement interface with a new blended ANN-PLS method.

The hospitality industry values segmentation and loyalty programs (LPs), but there is limited research on new methods for segmenting loyalty program members, so managers often rely on conventional techniques. This study aims to use big data-driven segmentation methods to cluster customers and provide a new solution for customer segmentation in hotel LPs.

Using the k-means algorithm, this study examined 498,655 profiles of guests enrolled in a multinational hotel chain’s loyalty program. The objective was to cluster guests according to their consumption behavior and monetary value and compare data-driven segments based on brand preferences, demographic data and monetary value with loyalty program tiers.

This study shows that current tier-based LPs lack features to improve customer segmentation, and some high-tier members generate less revenue than low-tier members. Therefore, more attention should be given to truly valuable customers.

Hotels can segment LP members to develop targeted campaigns and uncover new insights. This will help to transform LPs to make them more valuable and profitable and use differentiated rewards and strategies.

As not all guests or hotel brands benefit equally from LPs, additional segmentation is required to suit varying guest behaviors. Hotel managers can use data mining techniques to develop more efficient and valuable LPs with personalized strategies and rewards.

This study aims to investigate the role of three customer equity drivers on customer repurchase intent in business-to-business (B2B) markets. It also explores the interconnected nature of equity drivers, specifically, the effects of brand equity and value equity on relationship equity. Further, it investigates how perceived switching costs moderates the interrelationships between customer equity drivers. The authors explore the interrelationships between the customer equity drivers in a B2B context involving commodity products in a developing market.

Data collection was done from a pool of 184 institutional customers of a lubricant brand in a developing market. The sample had representations of buyer organizations across sectors, namely, automobile, cement, metal, fertilizer, railway, defence and mining, etc. The final data were subjected to partial least squares-based structural equation modeling to test the hypothesized model.

The study found a direct effect of brand equity, and value equity on relationship equity and an indirect effect on repurchase intent, namely, relationship equity. Perceived switching cost was found to moderate the interaction between brand equity and relationship equity as well as between value equity and relationship equity. The direct effect of relationship equity on repurchase intent was also significant.

The study implies that B2B firms should ground their marketing program on these customer equity drivers, especially when dealing with commodity products. The absence of any of these drivers would be detrimental in customer retention. The study also establishes the relevance of switching cost(s) and its impact on the underlying dynamics between the different equity drivers in the context of commodity products. The customer equity drivers along with switching costs, if managed well, may become switching barriers for customers and eventually would ensure recurring revenue through repeat purchases.

To the best of the authors’ knowledge, this is one of the first studies that focuses on the disaggregated effect of customer equity on customer outcomes in the B2B context. Furthermore, this study investigates how perceived switching costs moderates the interrelationships between customer equity drivers in the industrial sales context in an emerging market.

Recent literature on customer engagement has introduced the concept of “actor engagement,” which serves as the foundation for this study. The study aims to investigate the formation of engagement and engagement's impact on the performance of sharing economy platforms in an international context.

The study analyses unstructured data from 145,434 service providers and 1,703,266 customers on Airbnb across seven countries (USA, Canada, United Kingdom, Australia, South Africa, China and Singapore). Machine learning techniques are used to measure actor engagement, and the research model is tested using structural equation modelling (SEM).

The findings suggest that actor engagement, encompassing the reciprocal relationship between customer engagement and service provider engagement, has a significant impact on platform performance. The moderator analysis highlights the role of cultural differences in the relationship between customer engagement and service provider engagement and between actor engagement and platform performance. Specifically, the study reveals that actor engagement exhibits a more pronounced impact on platform performance in Western countries (such as the USA, Australia and the UK), compared to Eastern countries (such as China and Singapore).

The analysis of the conceptual model is based on the utilisation of behavioural data obtained from the Airbnb website. Due to the nature of the available data, proxies are employed as measures for variables such as platform performance.

This research is amongst the first to provide empirical evidence for actor engagement formation and the function's role in platform performance in the sharing economy. The global nature of Airbnb as a platform facilitates the investigation of country-level factors, specifically cultural values, across seven diverse countries and highlight differences from business to customer (B2C) business models.

The purpose of this paper is to investigate the impact of customer-focus on small medium enterprise (SME) performance from the perspective of a resource-based view (RBV).

This research study implemented a survey strategy to gather data from 255 respondents on the registered list of Ghana Enterprise Agency (GEA) in the eastern region of Ghana. Scales used to gather data were operationalized from previous research studies. A structural equation modeling (SEM) path analysis was used to estimate the impact of customer-focus on the performance of SMEs.

The outcomes of this study indicate that customer-focus has a significant positive impact on SME performance, hence backing the current demand for investigating the distinct influence of customer-focus on SME performance. The results show that customer-focus has a positive and significant relationship with financial performance, customer performance, internal business process performance and learning and growth performance, thus supporting the literature on the positive impact of customer-focus on SME performance. Therefore, customer-focus determinants used in this study, including co-creation, networking ties, customer insight and artificial intelligence marketing (AIM), are critical to the optimization of SME performance.

Notwithstanding the importance of this research study mentioned earlier, the study has limitations. Notably, the sample size of this study can be increased to capture SME respondents in other geographical zones that were not included in this study. Future research studies may address how business environment conditions moderate the relationship between customer focus and performance, and also the cause-effect of the relationship between customer focus and business environment conditions on SME performance.

The practical implications consist of two main items. First, this study empowers SME owners and managers to develop a customer focus technique as a central strategic goal in their quest for SME performance optimization. Second, SME owners and managers should progressively exploit the four determinants of customer focus which include co-creation, networking ties, customer insight and (AIM in order to accrue important resources for effective utilization of their customer focus competences as a way to enhance their performance.

This study is targeted at the sound development of SMEs to bring about poverty alleviation and employment. Poverty, unemployment and poor living standards are recognized as vital social challenges in most emerging economies. The establishment of customer focus as an important strategic capability provides opportunities for SME survival, profitability and growth.

Generally, the findings of this research study provide a strong backing to RBV perspective and the proposition that customer-focus and its determinants (i.e. co-creation, networking ties, customer insight and AIM) should be acknowledged as a vital strategic resource for optimizing the performance of SMEs. This research study also provides new knowledge contribution to the present body of knowledge on customer-focus orientation and management literature, particularly in the context of an emerging economy.

Today's marketing is dominated by decision-making based on artificial intelligence and machine learning. This study focuses on one semi- and unsupervised machine learning technique, generative adversarial networks (GANs). GANs are a type of deep learning architecture capable of generating new data similar to the training data that were used to train it, and thus, it is designed to learn a generative model that can produce new samples. GANs have been used in multiple marketing areas, especially in creating images and video and providing customized consumer contents. Through providing a holistic picture of GANs, including its advantage, disadvantage, ethical considerations, and its current application, the study attempts to provide business some strategical orientations, including formulating strong marketing positioning, creating consumer lifetime values, and delivering desired marketing tactics in product, promotion, pricing, and distribution channel. Through using GANs, marketers will create unique experiences for consumers, build strategic focus, and gain competitive advantages. This study is an original endeavor in discussing GANs in marketing, offering fresh insights in this research topic.