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As e-commerce has expanded rapidly, online shopping platforms have become widespread in India and throughout the world. Product return, which has a negative effect on the E-Commerce Industry's economic and ecological sustainability, is one of the E-Commerce Industry's greatest challenges in light of the substantial increase in online transactions. The authors have analyzed the purchasing patterns of the customers to better comprehend their product purchase and return patterns.

The authors utilized digital transformation techniques-based recency, frequency and monetary models to better understand and segment potential customers in order to address personalized strategies to increase sales, and the authors performed seller clustering using k-means and hierarchical clustering to determine why some sellers have the most sales and what products they offer that entice customers to purchase.

The authors discovered, through the application of digital transformation models to customer segmentation, that over 61.15% of consumers are likely to purchase, loyal customers and utilize firm service, whereas approximately 35% of customers have either stopped purchasing or have relatively low spending. To retain these consumer segments, special consideration and an enticing offer are required. As the authors dug deeper into the seller clustering, we discovered that the maximum number of clusters is six, while certain clusters indicate that prompt delivery of the goods plays a crucial role in customer feedback and high sales volume.

This is one of the rare study that develops a seller segmentation strategy by utilizing digital transformation-based methods in order to achieve seller group division.

Grounded in contingency theory and strategic fit theory, the goal for this research was to determine if managers differentiate in terms of the degree of partnership when allocating resources for planning, joint operating controls, communication and other management components to relationships and if this differentiation is based on the Partnership Model (Lambert et al., 1996).

In total, 381 managers representing 31 relationships participated in one-and-a-half-day partnership meetings, and the authors analyzed how the management components were implemented in each relationship compared to the recommendations in the Partnership Model.

Managers did not differentiate types of partnerships which led to over-resourcing relationships with low potential and under-resourcing those with the highest potential for creating value. The principles of contingency theory and strategic fit were not used for managing relationships.

Contingency theory combined with the relationship view suggests that management components should not be implemented at the same level for all relationships, but in the 31 relationships studied different partnership types were not managed based on their potential.

The research reinforces the need for a formal structure like the Partnership Model to establish joint goals for a relationship and guide management in implementation.

Effective supply chain management depends on the ability of managers to differentiate among partnership types and fit relational mechanisms that are appropriate. However, researchers tend to generalize their findings to all partnerships regardless of potential. The authors found support for the Partnership Model published in IJLM in 1996 as a method to resource different types of partnerships following the contingency perspective and strategic fit theory.

Customer transformation is currently overlooked in service research. This article aims to conceptualize customer transformation and develop a research agenda to encourage more exploration in this area.

This conceptual article builds on the literature on transformation and related topics in psychology, sociology, education and anthropology.

The presented definition of customer transformation distinguishes itself from other related concepts such as minor change. The research agenda, structured around five themes, reveals four distinctive attributes of customer transformation that warrant academic investigation. These include the inability of businesses to guarantee transformations, the potential tension between transformational aspirations and immediate needs and well-being, the imperative of cultivating long-term engagement and the likelihood of encountering customer resistance. This highlights the criticality of embracing a customer-centric approach in transformational services.

Given the vastness of the topic, the literature review is limited and the research agenda could be widened. Furthermore, the dynamic nature of the subject introduces the possibility that the conceptual framework and research agenda may become outdated. Lastly, the universal applicability of the findings and the proposed conceptual framework are uncertain, necessitating potential validation across diverse contexts. The practical implications may also fall short of addressing the specific challenges encountered by different industries or businesses.

The article provides insights on customer transformation and strategies for businesses to support ongoing transformations, emphasizing personalized engagement and co-creating value to meet evolving customer aspirations.

The need for development and growth is more pressing and decisive than ever. This need is often not well understood and, as a result, is not addressed by either scholars or companies. This paper helps address that social need.

The research enriches the service literature by paving the way for a crucial subfield in service research. Additionally, it establishes a shared understanding of customer transformation by highlighting its distinct characteristics and analyzing their implications for service management, proposing a conceptual framework and research agenda.

In an era where complex technological advances increasingly govern service delivery, it is incumbent on service firms to pioneer innovative strategies to sustain customer engagement and cultivate loyalty. This conceptual paper examines the transformative potential of artificial intelligence (AI) in the realm of online customer communities, with a particular focus on its creation, management and enhancement facets. The authors explore how AI can revolutionize the dynamics of customer interaction, feedback mechanisms and overall engagement within the service industry.

This conceptual paper draws from marketing and management literature focusing on customer communities and AI in service and customer engagement contexts with a robust future research agenda.

A classification of online customer community engagement is provided along with a conceptual framework to guide our understanding of the integration of AI into online customer communities.

This exploration underscores the imperative for service firms to embrace AI-driven approaches to online customer community management, not only as a means to optimize their operations but as a vital strategy to stay competitive in the ever-evolving digital landscape. This paper examines the novel combination of AI with online customer communities and provides the framework in the form of an input-process-output (IPO) model for future research into this integration.

In industrial buyer–supplier relationships, being an attractive customer has been found to result in superior supplier performance. However, there is a limited understanding of how these benefits transfer to the public domain. This study aims to explore the influence of customer attractiveness on supplier resource mobilization efforts toward the public sector.

A qualitative approach was used, focusing on in-depth interviews with 23 informants from 3 critical and complex supplier markets. The data were processed using inductive coding and thematic analysis.

The findings indicate that customer attractiveness in the public sector influences suppliers’ mobilization efforts on several dimensions. In addition to stimulating competition in the tender phase, customer attractiveness can yield important benefits to quality, supply stability and innovation during the business relationship. It appears imperative for the public sector to improve its standings with suppliers to both mitigate the apparent risk of sub-par treatment and to unlock the preferential supplier treatment associated with being an attractive customer.

Receiving increased mobilization from suppliers will result in better use of public money and help improve resilience and innovation in public procurement.

This study extends the research on customer attractiveness in the public sector by being the first to explore the range and nature of its influence on supplier mobilization efforts.

Service research offering a view of both the dark and bright sides of smart technology remains scarce. This paper embraces a critical perspective and examines the conflicting outcomes of smart services on the customer experience (CX), with a specific focus on chatbots.

This study uses empirical research methods to examine a single case study where an online retail service provider implemented a chatbot for customer service. Using discourse analysis, we analysed 7,167 conversations between customers and the chatbot over a two-year period.

The analysis identifies seven general themes related to the effects of the chatbot on CX: interaction quality, information gathering, procedure literacy, task achievement, digital trust, shopping stress and shopping journey. We illuminate both positive (i.e. having a pleasant interaction, providing information, knowing procedures, improving tasks, increasing trust, reducing stress and completing the journey) and negative outcomes (i.e. having an unpleasant interaction, increasing confusion, ignoring procedures, worsening tasks, reducing trust, increasing stress and abandoning the journey).

The paper develops a comprehensive framework to offer a clearer view of chatbots as smart services in customer care. It delves into the conflicting effects of chatbots on CX by examining them through relational, cognitive, affective and behavioural dimensions.

Drawing on the conservation of resources theory, this study aims to identify the mediating effects of depersonalization and resilience on the relationship between customer incivility and organizational citizenship behavior (OCB). It further posits that these indirect effects vary depending on the caring climate and achievement orientation.

A field survey among 622 service employees (Study 1) and a three-wave field survey of 315 service employees and their managers (Study 2) from various service organizations were conducted.

This study confirms that depersonalization operates as a negative mediator in the relationship between customer incivility and OCB. Simultaneously, resilience emerges as a positive mediator, underscoring the contrasting pathways through which customer incivility affects OCB. Furthermore, a caring climate plays a pivotal role in mitigating the detrimental impact of depersonalization on OCB and weakening the positive impact of resilience on OCB. Additionally, this study identifies achievement orientation as a significant moderator between customer incivility and resilience.

This study advances theoretical foundations by investigating depersonalization and resilience as critical mediators in the intricate relationship between customer incivility and OCB. It goes beyond the conventional understanding of customer incivility’s impact by shedding light on the dual roles of a caring climate, demonstrating its potential to alleviate both positive and negative consequences of customer incivility. Moreover, its identification of achievement orientation as a moderator adds a novel dimension to the discourse, emphasizing the need for tailored strategies to harness employee resilience in the face of customer incivility.

The demand for healthcare innovation is increasing, and not much is known about how entrepreneurial firms search for and sell to customers in the highly regulated and complex healthcare market. Drawing on effectuation perspectives, we explore how entrepreneurial digital healthcare firms with disruptive innovations search for early customers in the healthcare sector.

This study uses a qualitative, longitudinal multiple-case design of four entrepreneurial Nordic telehealth firms. In-depth interviews were conducted with founders and senior managers over a period of 27 months.

We find that when customer buying conditions are highly flexible, case firms use effectual logic to generate customer demand for disruptive innovations. However, under constrained buying conditions firms adopt a more causal approach to customer search.

Managers need to gain a deep understanding of target buying environments when searching for customers. In healthcare sector markets, the degree of flexibility customers have over buying can constrain them from engaging in demand co-creation. In particular, healthcare customer access to funding streams can be a key determinant of customer flexibility.

We contribute to effectuation literature by illustrating how customer buying conditions influence decision-making logics of entrepreneurial firms searching for customers in the healthcare sector. We contribute to entrepreneurial resource search literature by illustrating how entrepreneurial firms search for customers beyond their networks in the institutionally complex healthcare sector.

This research paper explores customer experience (CX) among low-literate customers in organized retail environments. It integrates theories from customer literacy, CX and patronage literature to understand CX comprehensively.

The study gathered data from 470 respondents using mall intercept and snowball sampling. Data analysis employed partial least squares (PLS) modeling.

The results indicate that all the dimensions do not have the same effect on CX. Answering calls for future research, the results establish CX's nomological validity by showing its positive influence on retail reputation, retail quality and satisfaction. However, it does not directly affect patronage but has an indirect influence through retail quality and satisfaction. Also, the authors conclude that retail quality and satisfaction are consequences of CX and not previously conceptualized proxies for it.

Conducting primary research with low-literate customers (LLCs) has its own set of limitations that give rise to further research directions. While acknowledging limitations, the study suggests avenues for future research by surveying LLCs with an objective questionnaire, contributing to limited empirical research in this segment.

The findings highlight the multidimensional nature of CX. In summary, this research paper provides insights into CX dimensions and outcomes for LLCs in organized retail. It contributes to marketing literature, assisting retailers in improving CX and driving patronage across customer segments.

The paper contributes to marketing literature by studying LLCs, testing a comprehensive CX model, confirming antecedents in retail patronage and exploring reciprocal relationships in retailing.

This study aims to use the voice of the customer (VoC) strategy to collect user-generated content (UGC) compare customer expectations with reality, make the necessary improvements for the business and create personalized strategies for each customer to maximize revenue, focus on hospitality industry in Vietnam market.

This study proposes a synthesis of techniques for a deep understanding of the VoC based on online reviews in the hospitality industry. First, 409,054 comments were collected from websites in the hospitality sector. Second, the data will be organized, stored, cleaned, analyzed and evaluated. Next, research using business intelligence (BI) solutions integrating three models, including net promoter score (NPS), graph model and latent Dirichlet allocation (LDA), based on natural language processing (NLP) technique, experiment on Vietnamese and English data to explore the multidimensional voice of customer’s row. Finally, a dashboard system will be implemented to visualize analysis results and recommendations on marketing strategies to improve product and service quality.

Experimental results allow analysts and managers to “listen to the customer’s voice” accurately and effectively, identify relationships between entities, topics of discussion in favor of positive and negative trends.

The novelty in this study is the integration of three models, including NPS, graph model and LDA. These models are combined based on the BI solution and NLP technique. The study also conducted experiments on both Vietnamese and English languages, which ensures more effective practical application.