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Usage of updated technology is continuously empowering customer relationship management (CRM) to be convenient and user friendly, where customers are kept engaged with knowledge and information. This enables them on decision-making and managing their portfolio, especially in mutual fund investments. To improve toward a positive decision, certain quality related variables needed to be considered. Thus, this study aims to estimate the mediation effect of relationship quality and outcome (RQO) between CRM and investment decision-making in mutual funds (MFD).

The descriptive study adopted the constructs from existing empirical literatures to conceptualize the model with three higher order constructs with 12 dimensions. Survey method is used, and with a structured questionnaire, a total of 323 mutual fund investors were approached using nonprobability criterion sampling technique, of which 262 relevant responses were considered for estimating the structural model. Smart PLS was used to establish the relationship of the constructs.

The result emphasizes a significant direct and indirect relationship indicating that investors are more inclined to MFD through technology-enabled CRM and RQO plays a vital role in explaining the direct relationship between CRM and MFD. The results of the study are in-line with the existing literature.

The study highlights that financial institutions must focus not only on technological diffusion but also needs to ensure quality service by providing knowledge and information during every access of transactions by customers, making them independent and confident during investments.

This study indicates how capacity efficiency, which is a part of service productivity, can be managed without affecting the outcome efficiency by incorporating technology in the place of human interaction during relationship acquiring and retaining process.

This paper aims to examine how customer participation in new service development (NSD) and customer relationship management (CRM) technology can improve the NSD performance of manufacturing firms. Additionally, the paper examines CRM technology usage to understand how it impacts new service performance both individually and jointly with customer participation in NSD.

This study is a survey of 216 manufacturing managers who are overseeing the development of new services at their organizations. For the analysis, structural equation modeling is used with Amos 22.0. Measures of all latent variables in the analysis pass the traditional tests for reliability, convergent validity and discriminant validity. Furthermore, the results of a common latent factor test for common method variance and Harman’s one-factor test indicate that common method bias is not a source of endogeneity in the model.

Customer participation has a positive effect on NSD performance. CRM technology usage also has a positive effect on NSD performance. The effect of customer participation on NSD performance is enhanced by CRM technology. The results of a post hoc analysis suggest that the usage of CRM technology has the most benefit for managing the technical aspects of customer participation.

This study has methodological limitations that may impact the generalizability of results. For instance, it is based on cross-sectional self-reported survey data, which is more subjective than longitudinal secondary data. Survey research lacks the depth and nuance of qualitative research designs, which are commonly employed to study NSD. In addition, this study focuses on large US manufacturing firms. The authors do not include small firms or international organizations in the sample. Despite these limitations, they believe the findings can provide significant contributions to the NSD literature.

Although prior research has shown that customer participation and CRM technology can individually influence new product development (NPD) performance, the results indicate they are equally effective factors in the development of new services. Furthermore, the authors show that customer participation can be enhanced via the use of CRM technologies. The interaction is more pronounced within the technical aspects of NSD.

This study contributes to the NSD literature, and it also has implications for managers leading NSD efforts in traditional tangible-product industries. The findings provide additional evidence that customer participation is an effective NSD strategy for manufacturing firms (Morgan et al., 2019). Furthermore, CRM technology is integral to NSD performance. CRM technology not only has a direct effect on NSD performance, but the interaction term of customer participation by CRM technology also has a positive effect on NSD performance.

The purpose of this study is to examine the impact of customer relationship management (CRM) components on competitive advantage through customer loyalty in the banking sector of Bangladesh.

A structured questionnaire was used for the data collection process. In all, 326 respondents were participated in the survey and selected conveniently from the commercial banks of Bangladesh. Data were analyzed by using Smart-PLS software.

The outcomes of this study indicate that customer orientation and technology capability have a positive impact on competitive advantage, while customer knowledge does not. Besides, customer loyalty significantly mediates the relationship between customer orientation and technology capability with competitive advantage, while this mediation effect appears insignificant between customer knowledge and competitive advantage.

This study's findings can help Bangladeshi bank managers communicate with new customers about their promotional activities while keeping old customers informed about new CRM initiatives.

This study adds to the existing pool of knowledge on CRM components, customer loyalty and competitive advantage literature. Particularly, the mediating role of customer loyalty between the CRM components (customer orientation and technology capability) and competitive advantage is the unique contribution of this research.

The purpose of this study is to examine the influence of knowledge creation (KC) process on customer relations management (CRM) in Palestinian commercial banks, taking into consideration which factors of KC process support the CRM system.

The study uses a quantitative research design wherein questionnaires have been used to collect data from 345 respondents in the Palestinian banking sector. Research hypotheses have been tested using multiple regression analysis.

The findings unveil that socialisation and combination processes have a positive impact on CRM. In contrast, internalisation process negatively affects CRM system, but outsourcing knowledge does not significantly affect CRM.

Past studies empirically validated the success of CRM adaptation in the context of different industries. This study provides a new conceptual model which validates the influence of KC on CRM in the banking sector. It also affirms the integral role of KC in supporting CRM from an emerging country perspective like Palestine.

This study offers new insights into creating of knowledge by employees in supporting CRM. It will encourage future scholars to further explore the key dimensions of the KC process for a more detailed investigation at a workplace. This study suggests that banks’ directors and employees should behave in a social manner to support relationship with customers. This study also suggests facilitating knowledge from different resources in innovative ways, through encouraging creative thinking from experiences, using technology in sharing knowledge, focussing on appropriate training to resolve customers' problems and disseminating new knowledge among employees.

This study expands the body of knowledge on KC process in supporting CRM from an emerging country perspective. This study validates the influence of KC on CRM in the Palestinian banking sector. This sheds light on the integration of these two concepts.

Based on relationship marketing theory, this study aims to test the effect of social customer relationship management (social CRM) on customer satisfaction (CS) and loyalty (CL).

To assess the proposed framework, structural equation modeling was performed on the data of 314 automotive customers surveyed online.

Social CRM dimensions [traditional CRM (TCRM) and social media (SM) technology use] have a direct and positive effect on CS. On the other hand, only TCRM has a direct and significant influence on CL, while the SM technology use effect seems to be indirect rather than direct. Indeed, the findings have provided empirical support for the contention that CS plays a mediating role between social CRM dimensions and CL.

In the automotive sector and developing countries in particular, companies’ managers could increase CS and CL and consequently enhance their competitiveness and market share by adopting an effective social CRM strategy. From this perspective, companies should focus their social CRM campaigns on the most SM used by customers, offer personalized choices and improve customer experience, interaction and value co-creation.

This paper enriches the understanding of how social CRM can affect CS and CL. The scales of social CRM, CS and CL were validated in the context of developing countries and the automotive sector. Furthermore, the direct and mediating effect of CS between social CRM (TCRM and SM) and CL was also confirmed.

Basándose en la teoría del marketing relacional, este estudio pretende comprobar el efecto de la gestión social de las relaciones con los clientes (CRM social) sobre la satisfacción y la fidelidad de los clientes.

Para evaluar el marco propuesto, se realizó un modelado de ecuaciones estructurales sobre los datos de 314 clientes de automoción encuestados online.

Las dimensiones del CRM social (CRM tradicional y uso de tecnología de medios sociales) tienen un efecto directo y positivo en la satisfacción del cliente. Por otro lado, solamente el CRM tradicional tiene una influencia directa y significativa en la fidelidad del cliente, mientras que el efecto del uso de la tecnología de medios sociales parece ser más indirecto que directo. De hecho, los resultados han proporcionado apoyo empírico a la afirmación de que la satisfacción del cliente desempeña un papel mediador entre las dimensiones del CRM social y la fidelidad del cliente.

Este artículo enriquece la comprensión de cómo el CRM social puede afectar a la satisfacción y la fidelidad de los clientes. Las escalas de CRM social, satisfacción del cliente y fidelidad del cliente se validaron en el contexto de países en vías de desarrollo y del sector automovilístico. Además, también se confirmó el efecto directo y mediador de la satisfacción del cliente entre el CRM social (CRM tradicional y medios sociales) y la fidelidad del cliente.

En el sector de la automoción y en los países en desarrollo en particular, los directivos de las empresas podrían aumentar la satisfacción y fidelidad de sus clientes y, en consecuencia, mejorar su competitividad y cuota de mercado adoptando una estrategia eficaz de CRM social. Desde esta perspectiva, las empresas deberían centrar sus campañas de CRM social en los medios más utilizados por los clientes, ofrecer opciones personalizadas y mejorar la experiencia del cliente, la interacción y la cocreación de valor.

基于关系营销理论, 本研究旨在检验社会化客户关系管理（social CRM）对客户满意度和忠诚度的影响。

为评估所提出的框架, 对 314 名汽车客户的在线调查数据进行了结构方程建模。

社交客户关系管理维度（传统客户关系管理和社交媒体技术使用）对客户满意度有直接的积极影响。另一方面, 只有传统客户关系管理对客户忠诚度有直接和显著的影响, 而社交媒体技术使用的影响似乎是间接而非直接的。事实上, 研究结果为客户满意度在社交客户关系管理维度和客户忠诚度之间发挥中介作用的论点提供了实证支持。

本文丰富了人们对社交客户关系管理如何影响客户满意度和忠诚度的认识。本文以发展中国家和汽车行业为背景, 对社会化客户关系管理、客户满意度和客户忠诚度的量表进行了验证。此外, 还证实了客户满意度在社会化客户关系管理（传统客户关系管理和社会化媒体）与客户忠诚度之间的直接和中介效应。

尤其是发展中国家, 企业管理者可以通过采取有效的社交客户关系管理战略, 提高客户满意度和忠诚度, 进而增强竞争力和市场份额。从这个角度来看, 企业应将社交客户关系管理活动的重点放在客户使用最多的社交媒体上, 提供个性化选择, 改善客户体验、互动和价值共创。

Customer lifetime value (CLV) is one of the key indicators to measure the success or health of an organization. How can an organization assess the organization's customers' lifetime value (LTV) and offer relevant strategies to retain prospective and profitable customers? This study offers an integrated view of different methods for calculating CLVs for both loyalty members and non-membership customers.

This study outlines eleven methods for calculating CLV considering (1) the deterministic aspect of NPV (Net present value) models in both finite and infinite timespans, (2) the geometric pattern and (3) the probabilistic aspect of parameter estimates through simulation modeling along with (4) the migration models for including “the probability that customers will return in the future” as a key input for CLV calculation.

The CLV models are validated in the context of complementary and alternative medicine (CAM)in the healthcare industry. The results show that understanding CLV can help the organization develop strategies to retain valuable customers while maintaining profit margins.

The integrated CLV models provide an overview of the mathematical estimation of LTVs depending on the nature of the customers and the business circumstances and can be applied to other business settings.

Scholars have affirmed that a conceptualization of value co-creation in business relationships should reflect the nature and characteristics of interactional processes that occur in use. The advent of sales and marketing technologies, however, is changing the nature and dynamics of interactions. New trends in digitalization have played a significant role in emphasizing and facilitating the occurrence of business-to- business (B2B) collaborative or sharing economy. The B2B sharing economy and value co-creation are closely intertwined, as businesses harness the power of shared resources and collaboration to generate value in diverse ways. This study highlights the importance of going beyond value co-creation in studying B2B collaborative economy, unpacking the interconnected value processes that influence value co-creation. It also aims at showing the activities that characterize multiple joint value spheres among actors.

The study consists of 49 qualitative interviews with managers operating in different industries.

The paper shows that when considering digital B2B contexts, five joint value spheres in business relationships should be considered: a value co-creation, a value appropriation, a value communication, a value measurement and a value representation sphere. Each one is characterized by specific activities that are relevant from a managerial point of view.

This study highlights that value co-creation has often been over stressed when discussing business interactions, also with the advent of new technologies. Rather, this study offers a more comprehensive view of value co-creation that includes different value processes occurring in joint value spheres. These further processes are relevant because failure and success in business relationships within the B2B sharing economy are often dependent from activities outside the value co-creation process, which strongly affect it. Such knowledge will also open up new research venues and opportunities to better contribute to the practice of value management in business relationships.

This paper aims to (1) identify the different performance drivers (lead indicators) and outcome measures (lag indicators) investigated in the literature concerning the four balanced scorecard (BSC) perspectives in operations management (OM) contexts and (2) understand how performance drivers and outcome measures (and substantiated perspectives) are related.

We undertake a systematic literature review of the BSC literature in OM journals. From the final sample of 40 articles, performance drivers and outcome measures have been identified, and the relationships amongst them have been synthesised according to the system dynamics approach.

Findings show (1) the most relevant performance drivers and outcome measures within each BSC perspective, (2) their relationships, (3) how the perspectives are linked through the performance drivers and outcome measures and (4) how the different measures relate systemically. Accordingly, four causal loops amongst identified measures have been built, which – jointly considered – allowed for the creation of a dynamic strategy map for OM.

This study is the first one that provides a comprehensive and holistic view of how the different performance drivers and outcome measures within and between the four BSC perspectives in OM relate systemically, increasing the knowledge and understanding of scholars and practitioners.

The low adoption of mobile banking (m-banking) in Indonesia and limited research on the adoption of m-banking motivate this research to understand the factors needed in developing m-banking to support the achievement of the national digital economy strategy in creating a digital ecosystem in Indonesia. This study aims to analyze the individual perspective factors that influence the adoption of m-banking applications in Indonesia.

This study used a quantitative approach using an online questionnaire to survey 444 respondents who used m-banking applications in Indonesia. The data obtained were processed using covariance-based structural equation modeling.

The results showed that health consciousness, the availability of resources, personal innovativeness and perceived information quality factors influenced the adoption of mobile banking applications in the static stage. In addition, this study found that one adoption stage could positively impact another adoption stage in adopting m-banking applications.

The development of m-banking can be promoted by considering the readiness of operational support infrastructure, regulations and application development, including functionality, security and user experience. Superior m-banking has implemented an end-to-end banking process with integrated customer relationship management (CRM) that supports cross-selling features according to user needs.

This study addresses the knowledge gap on individual perspectives that influence m-banking applications adoption. The authors integrate the e-government adoption model and CRM model in this study.

This study aims to predict customer churn in resort hotels by calculating the churn probability of repeat customers for future stays in the same hotel brand.

Based on the recency, frequency, monetary (RFM) paradigm, random forest and logistic regression supervised machine learning algorithms were used to predict churn behavior. The model with superior performance was used to detect potential churners and generate a priority matrix.

The random forest algorithm showed a higher prediction performance with an 80% accuracy rate. The most important variables were RFM-based, followed by hotel sector-specific variables such as market, season, accompaniers and booker. Some managerial strategies were proposed to retain future churners, clustered as “hesitant,” “economy,” “alternative seeker,” and “opportunity chaser” customer groups.

This study contributes to the theoretical understanding of customer behavior in the hospitality industry and provides valuable insight for hotel practitioners by demonstrating the methods that facilitate the identification of potential churners and their characteristics.

Most customer retention studies in hospitality either concentrate on the antecedents of retention or customers’ revisit intentions using traditional methods. Taking a unique place within the literature, this study conducts churn prediction analysis for repeat hotel customers by opening a new area for inquiry in hospitality studies.