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This study aims to investigate the association of FinTech innovation (FinTechINN) and firm performance (FP) by considering the role of knowledge assets (KA) as a causal mechanism underlying the FinTechINN – FP association.

In this study, the authors consider panel data of 1,049 Chinese A-listed firm and construct a structural model for corporate FinTech innovation, knowledge assets and firm performance while considering endogeneity issues in analyses over the period of 2014–2022. The modified value added intellectual capital (VAIC) and research and development (R&D) expenses are used as a proxy measure for knowledge assets, considering governance and corporate performance measures.

According to the findings of this study FinTech innovation (FinTechINN) has a positive significant effect on firm performance. Particularly; the findings disclose that FinTech innovations has a link with knowledge assets, FinTech innovations indirectly affects firm performance, and the association between FinTech innovation and firm performance is partially mediated by knowledge assets (MVAIC and R&D expenses).

Rooted in the dynamic capability and resource-based view, this study pioneers an empirical exploration of the association of FinTech innovation with firm performance. Moreover, it introduces the novel dimension of knowledge assets (on firm-level), acting as a mediating factor with in this relationship.

This chapter discusses the theoretical framework of the strategic knowledge creation process for realizing business innovation. It presents an explanation of the relationship between the concept of the business community that originates with the formation of “Ba” (which is required in the formulation and execution of the strategic knowledge creation process) and the strategic knowledge creation process. The chapter also analyzes and examines the theoretical framework where the holistic leadership of practitioners achieves new business innovation through the formation of a business community, which is the organizational platform for practicing strategic knowledge creation, that is, the sharing, inspiration, creation, and stockpiling of knowledge.

In particular, the chapter presents a dynamic, theoretical framework where all practitioners at every level of management demonstrate holistic leadership across a three-layered structure (three practice layers) including the formal organization layer, the informal organization layer, and the psychological boundary layer to connect elements for formulating and executing macro and micro strategies and the business community, which has its origins in the formation of “Ba,” to drive the strategic knowledge creation processes.

This study aims to build upon resource orchestration theory to theorize and empirically test a model that demonstrates how knowledge assets and innovation ambidexterity trigger a synergy in favor of firm performance.

Drawing on a survey of 158 Iranian knowledge-intensive companies, this study uses the partial least squares based on structural equation modeling to test the research hypotheses.

The results show that two elements of knowledge assets, namely, structural and relational capital, indirectly affect firm performance through the full mediation of innovation ambidexterity. The findings indicate that human capital has no relationship with both innovation ambidexterity and firm performance.

This study offers fresh insights into the issue of how organizations can create value from an effective orchestration of various strategic resources and capabilities, including knowledge assets and innovation ambidexterity.

This study applies resource orchestration theory to concurrently the areas of knowledge resources and organizational ambidexterity to show how innovation ambidexterity plays a role in translating three various knowledge assets into performance.

The pivotal role of knowledge management (KM) and its extensive implications have been debated in the academic literature with insufficient focus on its link to particular organizational control mechanisms such as performance measurement systems (PMS). To bridge this gap and building on resource orchestration theory, this paper aims to investigate the relationships between KM factors, PMS and corporate performance.

Based on a survey data set of 92 listed companies in Iran, the framework and hypotheses were tested using structural equation modeling (SEM) based on partial least squares (PLS).

The SEM-PLS results indicate that knowledge assets are significantly associated with both PMS and corporate performance while knowledge process capabilities (KPC) are not significantly associated with PMS and corporate performance. This study also shows that PMS mediates the relationship between knowledge assets and corporate performance.

The results suggest that the use of appropriate management control systems plays an effective role in synchronizing, aligning and orchestrating a company’s various knowledge resources, which, in turn, can lead to superior overall performance.

Building on a unique synthesis of resource orchestration theory and the knowledge-based view of the firm, the results of this study provide the first empirical evidence on how PMS intervenes in the relationship between knowledge resources (knowledge assets and KPC) and corporate performance.

Organizational knowledge assets have been identified as sources of competitive advantage. It is therefore critical that organizations understand how they impact on performance in order to effectively manage these assets. This paper aims to extend the “knowledge‐value chain”, recently introduced in the management literature, by integrating the concept of dynamic capabilities. Based on a systematic review of the literature it seeks to demonstrate the important role of dynamic capabilities in the relationship between knowledge asset management and firm performance. This paper aims to argue that the effective management of knowledge asset enhances the value of organizational competencies, which in turn support organizational processes, products and services. Dynamic capabilities take the role of continuously shaping operating routines and competencies, and consequently deliver superior long‐term performance.

The central objective of the article is to extend the work presented by Carlucci et al. with the concept of dynamic capabilities. Carlucci et al. introduce the “knowledge value chain” as a model linking knowledge assets with firm performance.

Based on an extensive systematic literature review, a recognized evidence‐based tool for theory building, the paper finds that dynamic capabilities represent a missing component in the relationship between knowledge assets and firm performance.

It is believed that the insights presented in this paper represent the theoretical basis for the development of a conceptual framework on how effective knowledge asset management affect the overall business performance and improve the value‐generating activity of a company.

The paper reveals that knowledge assets interact with each other through learning mechanisms and knowledge management processes enable the generation of new knowledge, and the development of organizational routines that form the building blocks of firm's competencies. These organizational competencies, hence, condition the efficiency and the effectiveness of business processes, and consequently the value of firm's products and services. Dynamic capabilities shape and systematically reconfigure organizational competencies, through assimilating new knowledge, and linking, organizing and integrating the generated knowledge into organizational routines.

Appreciating the limited empirical research in the knowledge management (KM) field, the purpose of this paper is to investigate the relationship between marketing knowledge management (MKM) and performance in Jordanian telecommunications organizations (JTOs).

A quantitative methodology is adopted in which a model is developed, and hypotheses are stated, in order to examine the proposed relationship between MKM assets and capabilities and JTOs' performance. A highly structured questionnaire is developed and distributed to a sample of 339 managers in JTOs. With a response rate of 92 percent, 312 questionnaires are returned; the number of valid and usable questionnaires is 292. Using exploratory and confirmatory factor analyses, MKM assets are classified into built‐ and invested‐in marketing assets, while MKM capabilities are classified into internal and external marketing capabilities. Furthermore, JTOs' performance is classified into three dimensions: market, customer, and financial performances. Structural equation modeling is utilised to test the stated hypotheses and model.

Empirical findings indicate that MKM assets and capabilities have a positive effect on the overall performance of JTOs, with all its dimensions. Built‐in marketing assets show the strongest influence on market performance, internal marketing capabilities show the strongest influence on customer performance, while external marketing capabilities show the strongest influence on financial performance. On the other hand and despite showing the least influence on financial and market performances, invested‐in marketing assets have maintained a positive relationship with all dimensions of JTOs' performance.

A holistic approach should be adopted when addressing MKM. MKM assets and capabilities should be applied collectively in a competitive manner that reflects on organizational performance. This requires constant consideration of available marketing assets and capabilities, with continuous investments in developing and acquiring marketing assets. While financial measures are generally used in assessing KM contribution, other non‐traditional measures should be applied in order to give a more realistic and holistic view of MKM contribution to organizational performance.

Focusing on MKM assets and capabilities, the paper introduces a new perspective of MKM in Jordan, as a developing country. While focusing on a special scope of KM, i.e. MKM, the paper provides further empirical support to the relationship between KM and organizations' multiple dimensions of performance. The fact that this is the first empirical study conducted in Jordan where KM research is relatively scarce, adds to its originality.

Measuring intellectual capital is on the agenda of most 21st century organisations. This paper takes a knowledge‐based view of the firm and discusses the importance of measuring organizational knowledge assets. Knowledge assets underpin capabilities and core competencies of any organisation. Therefore, they play a key strategic role and need to be measured. This paper reviews the existing approaches for measuring knowledge based assets and then introduces the knowledge asset map which integrates existing approaches in order to achieve comprehensiveness. The paper then introduces the knowledge asset dashboard to clarify the important actor/infrastructure relationship, which elucidates the dynamic nature of these assets. Finally, the paper suggests to visualise the value pathways of knowledge assets before designing strategic key performance indicators which can then be used to test the assumed causal relationships. This will enable organisations to manage and report these key value drivers in today's economy.

The paper seeks to develop a business model that shows the impact of operational knowledge assets on intellectual capital (IC) components and business performance and use the model to show how knowledge assets can be prioritized in driving resource allocation decisions.

Quantitative data were collected from 84 high‐tech federal contractors in the Washington DC metro area. Respondents in the target population were middle‐level and operations managers of business sectors holding positions as presidents, vice‐presidents, directors, engineering managers, operations managers, and analysts. Partial least squares (PLS) analysis was performed to develop a structural model between operational knowledge assets and IC components that maximizes explained variance for business performance. Operational assets were specified as formative constructs and IC and business performance were specified as reflective constructs.

A parsimonious conceptually sound model with significant measured variables and path coefficients was developed that explains almost 40 percent of the variance in business performance. The model shows both the interrelationships between the IC components that drive performance and the operational assets as levers for each IC component, respectively.

The scope of the study was focused on the high‐tech federal contractors in the USA. However, the model can be applied and tested in different industry sectors. This would provide evidence of the different operational knowledge assets used as levers in different industry sectors.

Senior executives and chief financial officers in particular are constantly challenged with making the optimum investment decisions given their budget constraints. The model offers a tool for developing and evaluating different resource allocation decisions based on an organization's strategic intent. In addition, the model can be useful in evaluating merger and acquisition decisions. In evaluating target companies the model can be used to identify the core capabilities or competency areas that the target company is leveraging and assess the impact or integration potential for the acquiring company.

This is the first study in the field of IC that has adopted the use of formative indicators in specifying operational knowledge asset constructs. Previous research has focused on developing models with the use of proxy measures as reflective indicators. Therefore the emphasis so far has been on scale development. The use of formative items in this study fills both the business need and theory gap to understand better the causal relationships that exist between work and knowledge assets.