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This study aims to explore the innovative strategies of business model of the free-to-fee switch, the relationship between the business model innovation and customer knowledge and further develop a conceptual model.

This study adopts a multiple case study method with abductive research logic, following the replication logic to select samples. A total of eight outstanding companies with altogether 312 free-to-fee switch events were selected from 1998 to 2021.

A strategic matrix with four innovative business models for the free-to-fee switch is generated. The parallelism between the models and customer knowledge orientations is also found. Further, the study develops the conceptual model regarding customer knowledge orientation as a key mediation.

The study highlights the conceptualization definition of customer knowledge orientation and its mediation effect to the business model innovation of free-to-fee switch, which is a new issue compared with previous research. Furthermore, it reveals that there exists organizational ambidexterity, which brings a new definition of customer knowledge orientation.

This study suggests how to integrate customer knowledge orientations to support the marketing process of the business model of free-to-fee switch. It also proposes a specific mechanism to conduct the free-to-fee switch with the introduction of four innovative strategic models and eight evolutional paths.

This study creatively proposes the strategic matrix and the conceptual model of business model innovation of free-to-fee switch. Moreover, a new conceptual definition of customer knowledge orientation is specified.

This paper aims to develop a theoretical framework for the conceptualization of customer experiential knowledge (CEK) by logically combining its different dimensions into one coherent explanatory concept. Drawing on the integration of the literature on customer experience, customer knowledge management and customer insights acquisition, supported by adequate empirical evidence, the framework provides a systematic, comprehensive and accurate understanding of CEK which, could contribute to the identification of relevant customer experience insights useful for customer knowledge management.

The analysis follows an inductive/deductive interpretative approach and it is based on a netnography of specialty coffee bloggers’ narratives in relation to their sustainability practices.

The paper identifies the following six types of CEK: normative, subcultural, epicurean, transcendental, subcultural and symbolic. Accordingly, CEK is defined as the knowledge tacitly possessed by customers in relation to how they live their consumption experiences according to a body of heterogeneous socio-cultural contextual factors (ethos, norms and symbols) and subjective influences (emotions, ingenuity, instincts and senses) deeply embedded into the narrative of a consumption experience.

While CEK has been largely observed and acknowledged, it has not been yet adequately addressed by existing research. The provision of a conceptual definition of CEK which emphasizes its different dimensions will be of use to both academics and practitioners to better identify and categorize the different manifestations of CEK when undertaking empirical observations or managerial decisions.

Building upon the insights of the resource-based view and internationalization theories, the purpose of this paper is to examine the role networks play in SMEs' readiness for internationalization. By investigating three different types of knowledge sharing, namely economic-setting, market-specific and customer-specific, the study analyzes their effect on SMEs' readiness for internationalization.

The four research hypotheses derived by from the analysis of the literature have been investigated by applying the multiple regression technique. By means of an online survey, 300 valid questionnaires were collected and information from a sample of Italian SMEs belonging to 11 agro-food consortia have been analyzed.

The results suggest that SMEs' readiness for internationalization could be supported by sharing customer-specific, market-specific and economic-setting knowledge with other firms operating within the same agro-food consortium. Additionally, data analysis highlights a negative relation between the risk perception in the process and readiness for internationalization, suggesting the importance of knowledge sharing in reducing the criticality issues of being a newcomer entering international markets.

From a theoretical perspective, this study aims to fill the gap in knowledge management and international relationship marketing literature. Since proposes a combination of different kinds of knowledge that contribute to reducing the criticalities SMEs must face by identifying useful information to be conveyed within the network. From a managerial perspective, the study provides useful insights for the agro-food sector, highlighting how experiential and network knowledge constitutes a pre-condition for managing internationalization complexity and discovering opportunities on foreign markets.

Due to the recent development of Big Data and artificial intelligence (AI) technology solutions in customer relationship management (CRM), this paper provides a systematic overview of the field, thus unveiling gaps and providing promising paths for future research.

A total of 212 peer-reviewed articles published between 1989 and 2020 were extracted from the Scopus database, and 2 bibliometric techniques were used: bibliographic coupling and keywords’ co-occurrence.

Outcomes of the bibliometric analysis enabled the authors to identify three main subfields of the AI literature within the CRM domain (Big Data and CRM as a database, AI and machine learning techniques applied to CRM activities and strategic management of AI–CRM integrations) and capture promising paths for future development for each of these subfields. This study also develops a three-step conceptual model for AI implementation in CRM, which can support, on one hand, scholars in further deepening the knowledge in this field and, on the other hand, managers in planning an appropriate and coherent strategy.

To the best of the authors’ knowledge, this study is the first to systematise and discuss the literature regarding the relationship between AI and CRM based on bibliometric analysis. Thus, both academics and practitioners can benefit from the study, as it unveils recent important directions in CRM management research and practices.

Drawing on resource and capability theory, this study aimed to analyze the relationship between the dynamic capabilities (DC), the knowledge management (KM) process (KMP) and results in customers and people. More specifically, the study argues that the KM process mediates the relationship between DC and the results outlined above. In addition, a predictive analysis is carried out that demonstrates the relevance of the KM process in the model.

The study sample is made up of 118 Spanish organizations that have some kind of recognition of excellence awarded by the European Foundation for Quality Management (EFQM). Partial least squares methodology is used to validate the research model, the hypothesis testing and the predictive analysis.

The results show that organizations which leverage the DC through the KMP improve customer and people outcomes. Moreover, the predictive power is higher when the KMPmediates the relationship between the DC and the results.

There is no consensus in the literature on the relationship between DC, KM and performance. Moreover, there are also not enough papers that study KM or DC through the dimensions that define these constructs or variables. Given this need, this work considers the KMP according to the stages of knowledge creation, storage, transfer and application. Similarly, DC is dimensioned in sensing, learning, integrating and coordinating capabilities. These, as reconfigurators of knowledge assets, influence the KMP. Accordingly, the empirical model connects these knowledge domains and analyses their link to outcomes.

Sustainable customer relationship management (SCRM) is a combination of business strategy, customer-oriented business processes and computer systems that seeks to integrate sustainability into customer relationship management. The purpose of this paper is to contribute to the body of knowledge of marketing, business management and computer systems research domains by classifying in research categories the current state of knowledge on SCRM, by analysing the major research streams and by identifying a future research agenda in each research category.

To identify, select, collect, synthesise, analyse and evaluate all research published on SCRM, providing a complete insight in this research area, the PRISMA methodology, content analysis and bibliometric tools are used.

In total, 139 papers were analysed to assess the trend of the number of papers published and the number of citations of these papers; to identify the top contributing countries, authors, institutions and sources; to reveal the findings of the major research streams; to develop a classification framework composed by seven research categories (CRM as a key factor for enterprise sustainability, SCRM frameworks, SCRM computer tools and methods, case studies, SCRM and sustainable supply chain management, sustainable marketing and knowledge management) in which academics could expand SCRM research; and to establish future research challenges.

This paper have an important positive social and environmental impact for society because it will lead to an increase in the number of green and socially conscious customers with an ethical behavior, while also transforming business processes, products and services, making them more sustainable.

Customer relationship management in the age of sustainable development is an increasing research area. Nevertheless, to the authors' knowledge, there are no systematic literature reviews that identify the major research streams, develop a classification framework, analyse the evolution in this research field and propose a future research agenda.

The primary purpose of this paper is to examine how generative Artificial Intelligence (AI) such as ChatGPT may serve as a new context for management theories and concepts.

The paper presents the analyses of selected management theories on decision-making, knowledge management, customer service, human resource management and administrative tasks and explains what may change after generative AI adoption.

The paper indicates that some management theories and concepts need to be studied in the generative AI environment that may influence managerial work at the strategic, functional and administrative levels.

This paper is an opinion piece article and does not refer to empirical data. It formulates some conclusions to further empirical research studies.

The paper analyzes selected management theories in a new technological setting. The paper also provides information about the functions of generative AI that are useful in understanding and overcoming how new technology may change organizations and management.

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.

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 purpose of this paper is to investigate the food and beverage automatic retail environment by analysing the impact of planograms, conceived as a visual merchandising practice and shopping time – the time spent making a purchase – as part of food consumer purchasing behaviour to further enrich the debate on the ability of companies to absorb customer knowledge.

A real-world experiment was conducted using a sample of 27,230 valid observations of consumer purchasing decision-making processes at automatic vending machines (AVMs). Data were collected by a shopper behaviour analytics system that allows for a better understanding of the AVM users' behaviour. Two sets of regressions were run to test the two hypotheses.

The experimental results demonstrated that planograms – the planned, systematic organisation of products in an AVM – positively impact food purchases. A planogram acts as a mediator in the relationship between shopping time and purchase, resulting in shorter shopping times and more purchases.

This work adds to the customer knowledge literature by focussing on customer behaviour in the food and beverage automated shopping environment. The shopper analytics technology adopted to collect real-time data leads to a better understanding of the purchasing behaviour of AVMs' users and provides new marketing and retail insights into AVMs' performance that retailers can use to improve their marketing strategies.