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This paper aims to address the use of modelling and simulation tools to enhance intangible process assets management by simulating and automating their characterization depending on their quality and impact on an organizational business goal.

The authors conducted a study comparing two simulation-based approaches to characterize intangible assets: system dynamics and agent-based simulation.

Strategic business studies have not yet considered the use of simulation techniques to characterize the intangible assets at length. The proposed solution introduces significant improvements for strategic data visualization, providing company stakeholders with a practical and helpful prism through which to view an easily adaptable, cheap and meaningful source of information about their company’s process assets, and their behaviour based on operation indicators.

This research offers decision-makers in knowledge-intensive organizations alternatives for effective strategic decision-making and for leveraging prospective views based on the specification of the organization’s knowledge. To do this, stakeholders will be able to use very promising low-cost simulation-based tools to create practical scenarios and potential situations that generate inputs for debate and decision-making by senior and middle management.

This paper reports an unprecedented comparative study of system dynamics and agent-based simulation to speed-up the characterization of the intangible process assets based on their quality and impact on strategic goals. It stresses the benefits and implications of the use of these techniques for better strategic management.

The purpose of this paper is to present the strategic intangible process assets characterization (SIPAC) methodology illustrated by an example of its application to the field of information technology (IT). This is a pioneering methodology for characterizing the impact and quality of intangible process assets and intellectual capital as levers to achieve organizational objectives. This strategic intellectual capital approach will help to identify both intangible assets and indicators geared to meeting organizational objectives. This is of vital importance since the success of an organization can be construed in terms of goal achievement.

The paper illustrates an example of the step-by-step application of the proposed methodology at an IT company. The aim is to describe its use in a real case so that other companies can benefit from the replication of the methodology used.

The proposed methodology (SIPAC) that the authors have designed and applied has been found to be useful and provide an insightful new point of view for strategic decision making in the IT industry taking into account intangible process assets.

The proposed methodology has been exemplified in a real case. This should help organizations to use the methodology to replicate the results.

Each and every organization has know-how represented by intangible assets. This paper meets an identified need to use intangible process assets as levers to help organizations achieve their business goals.

The current scenario is dominated by an urgent need for economic recovery caused by the global health emergency that has been at work since January 2020. Digital transformation plays a crucial role in bringing about this recovery. However, the failure rate of digital transformation projects over the last 10 years is very high. Considering the growing demand for digital transformation from businesses, the digital transformation failure rate, if unchanged, could lead to an exponential growth in technical debt. Technical debt is acquired when the digital transformation to be deployed at a business fails. The accumulation of technical debt will lead not only to economic stalemate but possibly also to yet another setback.

The developed set of methodologies form what has been termed the Digital Transformation Governance Engineering Process (DTGEP). This process can help any business wishing to undertake a digital transformation project to materialize their project in a sustainable, productive and competitive way.

DTGEP prevents the generation of technical debt because organizational knowledge is aligned with the technological solution that best suits the needs of each business in order to support its strategic or business objectives.

DTGEP has already been used to successfully discover the relationship between business features and the prospective digital transformation. However, it needs to be applied in case studies on many other businesses across the economy in order to gather more accurate information that could be clustered by sectors.

DTGEP was tested on a set of 25 projects, and this paper reports several interesting findings regarding its use, like the impact of the digital transformation on different parts of the business model canvas (BMC) and the intellectual capital of the organization developing the digital transformation, and how the status of the organization's intangible assets affects the decision-making process with respect to the prospective digital transformation.

Information technology/software (IT/SW) professionals use the business model canvas (BMC) to identify innovative digital solutions that improve their client’s business values. This paper aims to address the issue of considering, for a client company, the status of its intangible assets (IAs) in decision-making on the most innovative digital solution.

This paper provides a method (BMCIA-method) and a simulation tool (BMCIA-NetSim) to help IT/SW professionals identify and assess an organization’s IAs and their impact on the BMC of digital business.

IT/SW professionals used this approach, at 14 small and medium-sized enterprises (SMEs), to identify innovative solutions and add digital value to their businesses. They used the BMCIA to provide their clients (SME’s chief executive officer or chief operating officer) with a view of the BMC enhanced with the status of IAs. These expressed interest in the use of the BMCIA and underscore its importance for making better decisions while aligning IT and the business. A survey reveals how well the BMCIA-method performed during its use to discover the best solution to be developed at each SME.

IAs affect the achievement of the business goal targeted using the BMC. If these are not identified, valued and properly aligned with the BMC blocks, critical information is hidden from the eyes of IT/SW professionals and their clients, preventing optimal decision-making on which is the best IT/SW solution to be implemented to add digital value to the client company.

This proposal is unique insofar as it outlines a simulation-based methodological and technical solution using software agents to simulate the impact of the intangible side of an organization on its business model.

The paper aims to develop a microcredit evaluation model (MEM) which could serve as a useful tool for banks and NBFIs when SMEs’ economic and financial risks are evaluated.

Based on the literature review, a set of 17 qualitative and quantitative prudential indicators is selected. Further, a calculation system is developed which relies on the multiple criteria analysis model elaborated by Altman (1968); starting from this, a matrix is developed and a rating system is built. The model is tested among six NBFIs which operate on the Romanian market; three of them are labeled by the Romanian Central Bank as the worst performers, while the other ones are qualified as the best performers. Data are collected from companies’ annual reports and also from the Ministry of Finance.

It proves that the MEM can serve as a useful tool for the national and international NBFIs’ risk assessment. It can anticipate NBFIs’ success or fall. Furthermore, its results can be guaranteed with a probability of 95 per cent, calculated through the VaR method. Last but not least, it can also be used by the international NBFIs which intend to enter in the Romanian market.

The present paper proposes an original model based on both quantitative and qualitative indicators organized in an integrative equation. The MEM helps both parties involved in the financial grant awarding process – NBFIs are able to better assess requests from SMEs, enabling them to increase the volume of granting, whereas SMEs are able to access money for development projects more easily.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

Part I of this chapter applies the principles of the philosophy of science and the derived scientific method to analyze the foundational concepts and core proposition of the Resource-Base View (RBV) as popularized by Barney (1986, 1991, 1997). This analysis identifies seven fundamental conceptual deficiencies and logic problems in Barney's conceptualization of “strategically valuable resources” and in Barney's VRIO framework for identifying strategically valuable resources that can be sources of sustained competitive advantage. Three problems – the Value Conundrum, the Tautology Problem in the Identification of Resources, and the Absence of a Chain of Causality – relate to the RBV's and VRIO's failure to provide an adequate conceptual basis for identifying strategically valuable resources. The Uniqueness Dilemma, the Cognitive Impossibility Dilemma, and an Asymmetry in Assumptions about Resource Factor Markets result in an inability of the VRIO framework to support identification of resources that can be sources of sustained competitive advantage. More fundamentally, the core proposition of the RBV – that resources that are strategically valuable, rare, inimitable, and organizationally embedded are sources of sustainable competitive advantage – is argued to result directly in the Epistemological Impossibility Problem that precludes use of the scientific method in RBV research. This chapter argues that until these conceptual deficiencies and logic problems are recognized and remedied, the RBV – in spite of its current popularity – is and will remain theoretically sterile and incapable of contributing in any systematic way to the development of strategy theory.

Part II of this chapter then suggests how foundational concepts developed within the competence perspective on strategy provide essential remedies for the identified deficiencies and problems in the RBV – and thereby provide a more conceptually adequate basis for representing the nature of firms in the scientific study of their interactions and competitive outcomes.

This article surveys available research on the contingent‐claims approach to risky debt valuation. The author describes both the structural and reduced form versions of contingent claims models and summarizes both the theoretical and empirical research in this area. Relative to the progress made in the theory of risky debt valuation, empirical validation of these models lags far behind. This survey highlights the increasing gap between the theoretical valuation and the empirical understanding of risky debt.

This chapter fills a significant gap in the intelligence literature and the knowledge sciences literature by aligning definitions and characterizations of knowledge capital as an essential intelligence source. The chapter also explains how knowledge capital might be leveraged in each of the four capabilities. The chapter presents a well-researched characterization of knowledge capital drawing from international scholars and practitioners’ work. The value of human capital, structural capital, and relational capital in intelligence work is explored.