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The study aims to design a holistic multi-stage hierarchical model that leverages the firm's knowledge-enabled distinctive core competencies (DCCs) and builds enduring and profitable customer relationships to achieve sustainable competitive advantage (SCA) in dynamic and challenging environments. It developed a knowledge-enabled customer-centric competitiveness strategy (KCCS) model that integrates four pillars: business process reengineering (BPR), knowledge management (KM), customer relationship management (CRM) and competitiveness strategy. It also proposed a BPR model to enable cross-functional cooperation and coordination for firms dealing with customers, provided a blueprint for KCCS's successful implementation and compared the KCCS model with other customer-centric (CC) approaches.

This study adopted an exploratory research design based on a literature review of relevant studies. It has systematically analyzed 130 articles and books from Scopus, the Web of Science, Google Scholar and other renowned databases from 1982 to 2022. The analysis involved identifying and selecting relevant literature and conducting thematic research to develop a theoretical KCCS model that integrates BPR, KM, CRM, competitiveness strategy and the firm's SCA into a KCCS model.

This study developed an integrative KCCS theoretical model rooted in the extant literature in BPR, KM, CRM, competitiveness strategy, DCCs, SCA and other fields. The study proposed a BPR model as a significant component of KCCS that enables cross-functional cooperation and coordination, which are often troublesome for firms in their dealings with customers. The study also provided a blueprint for successfully implementing the KCCS model and compared the KCCS model with other CC approaches.

This study filled many research gaps in the literature in which knowledge-enabled CC frameworks are widely scattered. It offered a conceptual multi-stage hierarchical KCCS model that combines interrelated elements of BPR, KM, CRM, and competitiveness strategy. It proposed a BPR model as a significant component of the KCCS that enables cross-functional cooperation and coordination, which frequently form barriers when dealing with customers. It also provided a blueprint for successfully implementing the KCCS and compared it with other CC approaches.

The present paper aims to propose a measurement scale of the customer knowledge enabled innovation (CKEI) capability.

Data were generated on the basis of in‐depth interviews with managers and was analysed using the “Sphinx” software.

A pool of 60 items is proposed for the eventual measurement of the CKEI capability.

The proposed measurement scale is still raw. Further research is needed in order to test its psychometric features as well as to validate its relevance into a general model of customer knowledge management and innovation.

Organizations need to measure the degree to which they are endowed with the capability of managing effectively customer knowledge in order to foster innovation. The CKEI scale is considered as a barometer allowing organizations to evaluate to what extent they are endowed with the capacity of co‐creating value with their customers. The proposed CKEI scale is believed to provide managers with the opportunity to regularly monitor their innovative capability and be close to their customers.

The CKEI capability is proposed as a new construct focusing on integrating both innovation and knowledge‐based capabilities literatures. The CKEI measurement scale is believed to extend these literatures and to add knowledge to these areas of research..

The purpose of this paper is to introduce the concept of customer knowledge-enabled innovation (CKEI) and suggests a scale for its eventual measurement. The process of the scale development is presented in detail following the Churchill (1979) paradigm. CKEI is defined as the capacity of the organization to introduce new products and services on the basis of effective management of customer knowledge. It reflects the degree to which the company is endowed with the expertise of managing properly customer knowledge in order to enhance innovation.

The CKEI raw scale is mainly composed of 57 items. In an effort to purify the scale measurement, test and validate its psychometric specificities, two surveys were administrated among two independent samples. Respondents were new product managers or marketing managers. One manager per firm was interviewed. The convenience sampling method was applied.

The CKEI scale has been intended to be uni-dimensional. It encompasses three main facets: the integrative capacity of the firm, the structural capacity and the internal management capacity. The developed scale is valid and highly reliable (composite reliability=0.90; variance extracted=0.5). After exploratory factor analysis and confirmatory factor analysis, a pool of ten items was retained for the eventual measurement of the CKEI scale.

CKEI has been tested in a Tunisian context; continued refinement of the proposed CKEI scale is, undoubtedly, possible and even desired, based on further research in other business environments. Such refinements and modifications could necessitate the inclusion of new items, or the deletion of original ones. In some cases, the hypothesized factor structure may need modifications. To keep abreast with the ever-changing business environment, the paper strongly urged to incorporate these relevant aspects in the scale into the future research, so that a valid measure of CKEI can be ensured on an ongoing basis.

The scale is offered to provide managers with a practical tool for the evaluation of their forces and weaknesses in managing customer knowledge in organizations. It is considered as a barometer allowing them to adjust and to modify continually their innovation strategies focusing on the intellectual capital management.

CKEI is a new concept that is introduced in this research as a knowledge-based capability which helps companies to sustain competitive advantage. The relevance of the CKEI is that it is considered as a dynamic capability integrating both innovation and customer knowledge management theories.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Introduces the concept of customer knowledge-enabled innovation. This practical tool provides a scale consisting of 57 items, which will enable bosses to evaluate strengths and weaknesses in their management of customer knowledge. It has been tried out on a range of companies in Tunisia.

The paper provides strategic insights and practical thinking that have influenced some of the world’s leading organizations.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

This paper aims to explore and conceptualize service recovery as an organizational capability. It proposes a new construct labeled knowledge-enabled recovery effectiveness (KERE).

Measures capturing the KERE construct were developed through domain identification, item pool generation using focus group interviews with managers involved in complaint management and content expert validation.

A first pool of 73 items was generated and then reduced to 37 items. Focus group interviews confirm the theoretical relevance of the KERE construct. Recovery culture, recovery process and internal recovery resources are the different components of a firm’s knowledge that serve as inputs, or as a source of a firm’s service recovery capabilities.

A quantitative study is needed in future research to assess the KERE’s construct structure and validity.

Managers may use the proposed scale to foster effective and relevant marketing strategies by setting clear policies that consider service recovery as a knowledge-based activity rather than a control targeted activity.

This research demonstrates the mutual dialogue between service recovery and knowledge-based capabilities. Also, it proposes a new concept labeled KERE and a raw scale to further understand firms’ aptitude in service recovery.

The purpose of this paper is to propose a methodology for conducting a knowledge‐enabled customer relationship management (KCRM) knowledge audit, which involves applying knowledge auditing principles to assess the existence and implementation level of KCRM processes within an organization. This type of audit enables an organization to thoroughly review the extent to which knowledge is generated, codified, distributed and utilized while the firm is identifying, differentiating between, interacting with, and customizing products and services for its customers.

This paper draws upon the KM, CRM, and auditing literatures to develop a KCRM knowledge audit methodology. As an illustration, the proposed methodology for KCRM knowledge auditing was applied within the service arm of a paint manufacturing firm in the United Arab Emirates (UAE).

The proposed methodology allows supplier organizations to systematically evaluate the extent to which their CRM approaches are knowledge‐enabled; and to identify competitive strengths and opportunities in the areas such as cost, product and service quality, as well as flexibility to meet the changing requirements of their business customers.

The study focused on a practical point of view and, therefore, there are no testable propositions derived. In addition, the study focuses on an explicit KM model, which has limitations in tacit KM such as social networks and detail guidelines of KM outcomes.

This paper draws upon the KM, CRM, and auditing fields to develop a KCRM knowledge audit methodology. It contributes to the KM, CRM, and auditing literatures by developing and demonstrating how these literatures intersect via the concept and methodology of a KCRM knowledge audit.

The purpose of the paper is to provide a thorough analysis of the concepts of business intelligence (BI), knowledge management (KM) and analytical CRM (aCRM) and to establish a framework for integrating all the three to each other. The paper also seeks to establish a KM and aCRM based framework using data mining (DM) techniques, which helps in the enterprise decision‐making. The objective is to share how KM and aCRM can be integrated into this seamless analytics framework to sustain excellence in decision making using effective data mining techniques and to explore how working on such aCRM system can be effective for enabling organizations delivering complete solutions.

This paper is based on focused and dedicated study of the literature present on the aCRM, KM and data mining techniques. The paper considered how to develop a strategy and operational framework that would build aCRM on the foundation of existing DM techniques and KM approach to meet the business challenges. Based on this research, a customized, integrated framework, to match the needs of business was designed.

KM focuses on managing knowledge within the organization and aCRM focuses on gaining analytical information from the customer data. Both KM and aCRM help in the decision making process and understanding. This knowledge is difficult to uncover. Hence, this paper explains the importance of data mining tools and techniques to uncover knowledge by the integration between KM and aCRM. This paper presents an integrated KM and aCRM based framework using DM techniques.

All the firms may not be in favor of adopting KM while implementing aCRM. The KM requires a convalesce of organizational culture, technology innovations, effective work force in culminating knowledge dissemination in all business domains.

The organizations implementing this knowledge enabled aCRM framework would be easily able to convert their business knowledge via the analytical CRM to solve many business issues, such as increase response rates from direct mail, telephone, e‐mail, and internet delivered marketing campaigns, increased sales and increased services. With aCRM, firms can identify their most profitable customers and use this knowledge for promotional schemes for those customers as well as identify future customers with prediction on ROI.

The need for the integration of KM and aCRM is clear. It is written for practitioners who are looking for approaches to improve business performance and maintain high profits for their business by incorporating knowledge‐enabled aCRM in their setup.

The objective of this paper is to highlight the importance of information technology in service recovery performance through the exploration of its influence on service recovery performance components and determinants.

A general inductive approach for analyzing qualitative data was adopted since the main research question of “How can information technology enable successful service recovery?” has not been examined in the complaint management literature. Data were collected through in‐depth interviews with key executives working in the Tunisian banking sector.

Drawing on the knowledge‐based view (KBV), the authors develop a general framework to understand the differences in service recovery performance (SRP). The research shows that various knowledge‐based resources such as customer orientation (CO), internal orientation (IO), and information technology (IT) complement one another to impact on SRP. Ignoring the complementarities of these resources in assessing SRP can seriously underestimate the impact of IT on the knowledge assets that are embedded in the firm recovery competency. This distinctive business competency is labelled knowledge enabled recovery effectiveness (KERE).

Given the exploratory nature of this study, these preliminary results need quantitative research to refine theory and measurement of service recovery capabilities and for future validation of the proposed framework.

The findings provide important implications for the effective design and the automation of complaint management and for the intervening mechanisms that govern the IT business value.

The paper examines the issue of complaint management from a knowledge based view and calls for the need to consider specific customer relationship management (CRM) areas as a set of knowledge based activities.

The concepts of customer relationship management (CRM) and knowledge management (KM) both focus on allocating resources to supportive business activities in order to gain competitive advantages. CRM focuses on managing the relationship between a company and its current and prospective customer base as a key to success, while KM recognizes the knowledge available to a company as a major success factor. From a business process manager’s perspective both the CRM and KM approaches promise a positive impact on cost structures and revenue streams in return for the allocation of resources. However, investments in CRM and KM projects are not without risk, as demonstrated by many failed projects. In this paper we show that the benefit of using CRM and KM can be enhanced and the risk of failure reduced by integrating both approaches into a customer knowledge management (CKM) model. In this regard, managing relationships requires managing customer knowledge – knowledge about as well as from and for customers. In CKM, KM plays the role of a service provider, managing the four knowledge aspects: content, competence, collaboration and composition. Our findings are based on a literature analysis and six years of action research, supplemented by case studies and surveys.

When can B2B firms improve product innovation capability (PIC) through customer participation (CP)? The purpose of this paper is to shed light on this interesting question by providing a framework to interpret how interorganizational relationships (IORs), including customer relationship commitments, firm’s relational capability and bilateral dependence structure moderate the relationship between CP and PIC.

A questionnaire survey is conducted among 376 business to business (B2B) firms located in mainland China. Six hypotheses on how IORs moderate the CP–PIC relationship are examined using hierarchical regression analysis technique.

The empirical research reveals that CP positively impacts PIC of B2B firms, which will be strengthened when either customer affective commitment, supplier’s relational capability or total interdependence is high. In addition, the relationship between CP and PIC weakens as customer’s calculative commitment or interdependence asymmetry strengthens.

This study enriches customer participation literature by highlighting the PIC outcomes of CP and examining the complex and contingent roles of the buyer–supplier relationship in moderating CP’s impact upon PIC.