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Increasingly, studies are reporting supply chain analytical capabilities as a key enabler of supply chain agility (SCAG) and supply chain performance (SCP). This study investigates the impact of environmental dynamism and competitive pressures in a supply chain analytics setting, and how intangible supply chain analytical capabilities (ISCAC) moderate the relationship between big data characteristics (BDC's) and SCAG in support of enhanced SCP.

The study draws on the literature on big data, supply chain analytical capabilities, and dynamic capability theory to empirically develop and test a supply chain analytical capabilities model in support of SCAG and SCP. ISCAC was the moderated construct and was tested using two sub-dimensions, supply chain organisational learning and supply chain data driven culture.

The results show that whilst environmental dynamism has a significant relationship on the three key BDC's, only the volume and velocity dimensions are significant in relation to competitive pressures. Furthermore, only the velocity element of BDC's has a significant positive impact on SCAG. In terms of moderation, the supply chain organisational learning dimension of ISCAC was shown to only moderate the velocity aspect of BDC's on SCAG, whereas for the supply chain data driven culture dimension of ISCAC, only the variety aspect was shown to moderate of BDC on SCAG. SCAG had a significant impact on SCP.

This study adds to the existing knowledge in the supply chain analytical capabilities domain by presenting a nuanced moderation model that includes external factors (environmental dynamism and competitive pressures), their relationships with BDC's and how ISCAC (namely, supply chain organisational learning and supply chain data driven culture) moderates and strengthens aspects of BDC's in support of SCAG and enhanced SCP.

This paper seeks to introduce an integrated framework to determine the relationships between organisation core competences and associated personal competencies.

At first organisation core competences are determined by conducting internal and external benchmarking exercises, respectively, employing the “collectiveness” and “uniqueness” measures using key capabilities as a basis. Subsequently a pair‐wise comparison using the Analytic Hierarchy Process (AHP) is conducted to assess related personal competencies using the Chartered Institute of Personnel and Development list of competencies. The paper shows how these individual competencies are crucial to the overall organisational core competences. The framework is tested for a construction company, where five management directors are interviewed to develop an overall picture regarding the strengths and weaknesses of the company's key capabilities.

Overall the results show that, despite being a construction company, the composition of its organisational capabilities is dominantly governed by intangible assets’ contributions. The AHP prioritisation analysis confirmed that with regard to Innovative solutions, organisational core competence, Customer focus, and Team orientation are the most related personal competencies.

This paper makes an original contribution in the core competence literature by showing how to evaluate individual competencies that are essential to the construction of the organisational core competence. The use of AHP facilitates consistent data by screening out any subjective anomalies. The outcome of this exercise can help management prioritise the most related personal competencies needed for developing its organisational core competences and to undertake crucial business functions.

Specific asset recognition rules often bar expenses for research and development (R&D) from recognition on corporate balance sheets. This tangible‐intangible accounting asymmetry has led to the development of intellectual capital reports (ICRs) for intangibles in general and for R&D in particular. Thus, two dichotomous reporting formats coexist in corporate disclosure. The purpose of this article is to bring together more closely the information on project intangibles from R&D provided by voluntary and mandatory reporting systems.

The authors used an experimental case study approach in a joint research project with a non‐university research and technology organisation (RTO). The methods deployed in the project included semi‐structured interviews, Delphi techniques and normative reasoning.

The results show that it is possible to use financial reporting's systematic approach and typical layout to ally the presumed strengths of financial reporting (i.e. the existence of standardised ways of interpretation and an educated readership) and indicator‐based ICRs (i.e. the capability of capturing the generic features of innovation activity).

Given the predominance of financial reporting's educated readership, it is useful to produce voluntary disclosures in such a form that the information can easily be embedded in the overall picture painted by financial numbers.

Inductive‐analytical ICRs are typically not intertwined with financial accounting. The article elaborates on linkages between financial accounting and inductive‐analytical reporting models and proposes a classification scheme for project intangibles from R&D based on information reliability.

This paper aims to bring together the existing theory from knowledge management (KM), competitive intelligence (CI) and big data analytics to develop a more comprehensive view of the full range of intangible assets (data, information, knowledge and intelligence). By doing so, the interactions of the intangibles are better understood and recommendations can be made for the appropriate structure of big data systems in different circumstances. Metrics are also applied to illustrate how one can identify and understand what these different circumstances might look like.

The approach is chiefly conceptual, combining theory from multiple disciplines enhanced with practical applications. Illustrative data drawn from other empirical work are applied to illustrate some concepts.

Theory suggests that the KM theory is particularly useful in guiding big data system installations that focus primarily on the transfer of data/information. For big data systems focused on analytical insights, the CI theory might be a better match, as the system structures are actually quite similar.

Though the guidelines are general, practitioners should be able to evaluate their own situations and perhaps make better decisions about the direction of their big data systems. One can make the case that all the disciplines have something to add to improving how intangibles are deployed and applied and that improving coordination between KM and analytics/intelligence functions will help all intangibles systems to work more effectively.

To the authors’ knowledge, very few scholars work in this area, at the intersection of multiple types of intangible assets. The metrics are unique, especially in their scale and attachment to theory, allowing insights that provide more clarity to scholars and practical direction to industry.

In the digital economy, as artificial intelligence applications increase, big data analytical capability (BDAC) plays a crucial role, and intellectual capital is growing in importance. This study aims to examine the possible benefits and effects of intellectual capital, BDAC and integrations on operational performance.

This study collected data from firms in Asia, and a total of 257 senior managers completed a questionnaire. Confirmatory factor analysis and structural equation modeling (SEM) is used for statistical analysis.

Intellectual capital positively correlates with BDAC, and BDAC positively relates to internal integration but not to external integration. Furthermore, both internal integration and external integration positively correlate with operational performance. This study supports that internal integration is a significant mediator in the influence of BDAC on operational performance.

First, the authors provide empirical evidence that intelligent capital in intangible resources helps firms to build BDAC. Second, this study stresses the importance of BDAC in business, which enhances the integration of the whole supply chain and results in superior operational performance.

This is a first attempt from the perspective of intelligent capital and uses SEM to emphasize the relationships among BDAC, supply chain integration and performance based on unique and irreplaceable intangible resources, thus providing a new perspective on the contributing factors of BDAC.

The strategic management literature emphasizes the concept of business intelligence (BI) as an essential competitive tool. Yet the sustainability of the firms’ competitive advantage provided by BI capability is not well researched. To fill this gap, this study attempts to develop a model for successful BI deployment and empirically examines the association between BI deployment and sustainable competitive advantage. Taking the telecommunications industry in Malaysia as a case example, the research particularly focuses on the influencing perceptions held by telecommunications decision makers and executives on factors that impact successful BI deployment. The research further investigates the relationship between successful BI deployment and sustainable competitive advantage of the telecommunications organizations. Another important aim of this study is to determine the effect of moderating factors such as organization culture, business strategy, and use of BI tools on BI deployment and the sustainability of firm’s competitive advantage.

This research uses combination of resource-based theory and diffusion of innovation (DOI) theory to examine BI success and its relationship with firm’s sustainability. The research adopts the positivist paradigm and a two-phase sequential mixed method consisting of qualitative and quantitative approaches are employed. A tentative research model is developed first based on extensive literature review. The chapter presents a qualitative field study to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. The study includes a survey study with sample of business analysts and decision makers in telecommunications firms and is analyzed by partial least square-based structural equation modeling.

The findings reveal that some internal resources of the organizations such as BI governance and the perceptions of BI’s characteristics influence the successful deployment of BI. Organizations that practice good BI governance with strong moral and financial support from upper management have an opportunity to realize the dream of having successful BI initiatives in place. The scope of BI governance includes providing sufficient support and commitment in BI funding and implementation, laying out proper BI infrastructure and staffing and establishing a corporate-wide policy and procedures regarding BI. The perceptions about the characteristics of BI such as its relative advantage, complexity, compatibility, and observability are also significant in ensuring BI success. The most important results of this study indicated that with BI successfully deployed, executives would use the knowledge provided for their necessary actions in sustaining the organizations’ competitive advantage in terms of economics, social, and environmental issues.

This study contributes significantly to the existing literature that will assist future BI researchers especially in achieving sustainable competitive advantage. In particular, the model will help practitioners to consider the resources that they are likely to consider when deploying BI. Finally, the applications of this study can be extended through further adaptation in other industries and various geographic contexts.

This paper aims to explore the relationship between corporate cultural/intangible assets and marketing capabilities by examining managers’ and entrepreneurs’ perceptions in a retail setting.

Nineteen face-to-face interviews were conducted with UK small and medium sized enterprise (SMEs) managers and entrepreneurs to identify six sub-capabilities that form marketing capability. The authors further validated the relationship between marketing sub-capabilities and its antecedent tangible and intangible assets. The qualitative approach used provided a deeper insight into the motivations, perceptions and associations of the stakeholders behind these intangible concepts, and their relationships with their customers.

The research identified that there is a strong relationship between tangible and intangible assets, their components and the following capabilities: corporate/brand identity management, market sensing, customer relationship, social media/communication, design/innovation management and performance management. In addition, companies need to understand clearly what tangible and intangible assets comprise these capabilities. Where performance management is one of the key internal capabilities, companies must highlight the importance of strong cultural assets that substantially contribute to a company’s performance.

Previous work on dynamic capability analysis is too generic, predominantly relating to the manufacturing sector, and/or focussing on using a single case study example. This study extends the concept of marketing capability in a retail setting by identifying six sub-capabilities and describing the relationship of each with tangible and intangible assets. Through extensive qualitative analysis, the authors provide evidence that by fully exploiting their embedded culture and other intangible components, companies can more favourably engage with their customers to attain a sustainable competitive advantage.

This paper aims to define a theoretical model that assesses and measures the intangible asset contribution to company performance. The model keeps in focus the most meaningful elements that reflect the success factors, crucial to company business strategy and value creation.

The model adopts a hierarchical structure. The strategic intangible assets of the company have been divided into value drivers; a series of measurement indicators have been selected to describe the characteristics of each aspect of the intangible company performance. The measurements obtained from numerical indicators, which express the totality of the results achieved by the organizational strategies, are combined to create the hierarchical assessment index (HAI), by assessing quantitative and qualitative company features, through the analytic hierarchy process (AHP).

The HAI identifies the sources of added value and competitive advantage in each business context; it traces the subordination of every element on company performance, and singles out those intangible assets that improve the company performance, at every level of the hierarchy.

The HAI provides guidelines to understand what are the key intangible factors to create the value of the company and suggests the implementation of corrective strategies.

The HAI is the expression of the combination of the objective measurements of intangible assets with the subjective contributions by the managers. In fact, besides the numerical results of the performance of every element in the hierarchical structure, the managers' opinions about the significance of their performance are also considered. Thus, objective and subjective evaluations jointly contribute to suggest the way to achieving the expected objectives.

The purpose of this study is to analyze the systematic relationships among dynamic capabilities in startups’ survival.

This study is based on a systematic literature review on dynamic capabilities related to startups’ survival, following the content analysis approach.

This study presents four different perspectives of analysis about dynamic capabilities from resources exchange and business factors that meet needs of startups' survival. It also points out new area for future research in this field. In doing so, this study differentiates itself by its approach not limiting dynamic capabilities research and enriching entrepreneurs' capability theory.

By indicating an evolution of dynamic capabilities theory among tangible and intangible resources exchange in a more favorable adaptation to startups growth, this study boosters and contributes to the society, economy in general and to the science of business management in various perspectives such as overcoming cognitive barriers, entrepreneur’s commitment, innovation capabilities and knowledge capacity of startups.

This study amplifies dynamic capabilities vision in startups’ survival as one of the main sources for growth in this type of organizations. It also develops a deeper understanding about new avenues for dynamic capabilities theory among tangible and intangible resources exchange.

The chapter is structured as follows: in the first part, we provide the framework for the analysis of the formation of the born global firm, whereas the entrepreneurial, strategic, and network-based factors are conceptually linked and leading toward a global champion. The analytical model proposes the analysis of strategic choices as defining factors at the level of entrepreneurial behavior, firm strategy, and network. The case study methodology is provided in the second part of the chapter. The third part provides the empirical linkages of entrepreneurial, strategy based, and network factors’ manifestations and underpinnings in R&D intensive entrepreneurial born global firms. These are followed by discussion and conclusions enclosing empirically grounded framework that explains the emergence of R&D intensive entrepreneurial-hidden champions from the perspective of entrepreneurial firm and network theories.