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In this paper, we investigate the stock market valuation of the intangible asset created by selling, general, and administrative (SG&A) expenditure. Although GAAP requires immediate expensing of SG&A, prior studies show that current SG&A generates future economic benefits, suggesting that it creates an intangible asset. We find that the contemporaneous stock market seems to recognize some of the intangible asset value implicit in SG&A. Positive subsequent returns can be earned in firms with a high SG&A intangible asset value. These excess returns are more likely due to investor mispricing than to risk compensation. Furthermore, we find that both analysts' long-term growth forecast revisions and one-year-ahead forecast errors are positively associated with the future value created by current SG&A, indicating that analysts partially incorporate the intangible SG&A asset value into their forecasts. Overall, the evidence suggests that the capital market only partially recognizes the intangible asset value created by SG&A expenditure.

Machine learning technology is widely used in the field of enterprise intangible value assessment due to its advantages in processing complex data and discovering linear relationships. This paper designs a B-P neural network model based on machine learning technology and compares it with the cost method, market method, income method, and option pricing B-S model for enterprise intangible asset value assessment. The performance of this paper’s model for predicting intangible assets is evaluated through enterprise transaction data collection and processing. In the training iteration of 40–80 rounds, this paper’s model loss, RMSE, accuracy, and recall successively converge to 0.08, 0.17, 0.91, and 0.96, and the relative error for the prediction of the value of enterprise intangible assets is low, which has a high performance in intangible value assessment. Additionally, this paper’s model computes the intangible asset value weights for various enterprises, and the results of expert judgments are essentially consistent. For instance, when analyzing human capital experts, the model calculates weights of 27.93% and 29.43%, respectively. This paper provides a scientific and accurate machine learning technology for enterprise intangible asset value assessment.

Purpose The competitive model has changed. In this context, society entered into an era in which intangible assets are the greatest assets of a company. However, some gaps and uncertainties are presented in the literature as to understand the value of a company based on knowledge intensive activities. The purpose of this paper is to analyze the methods of evaluation of intangible assets in the context of business, economic and strategic management. Design/methodology/approach This is a qualitative research. This research is characterized as descriptive, bibliographic, inductive. Findings The main results of this research can highlight the existence of valuation methods of intangible assets intended for specific industries, as public and/or private, that can be better aligned to the context of business; economic and/or strategic management. Originality/value It was found that intangible assets are a current topic and increasingly addressed in the literature.

Purpose>This study aims to investigate the impact of digital technologies for intangible assets management. The authors analyse how technological innovations and regulations of intellectual property affect business models of companies or intellectual property rights (IPR) intensive industries to determine the impact of digital transformation on intangible assets management, highlighting emerging issues and future effects of the digital technology revolution.Design/methodology/approach>The authors use a case study method to answer our research questions. The authors use Soundreef SpA as our case study, a collecting company that develops technology for monitoring, collecting and maximising the earnings of songwriters and music publishers. The authors also elaborate and adopt the framework of the enhanced intellectual capital as the theoretical lens for presenting and analysing our case study, determining how the digital transformation caused business model innovation and more transparent and timely performance measurement in copyright-based companies.Findings>The analysis of Soundreef SpA’s business model allows us to demonstrate how using new technologies drives the performance measurement of copyright holders and improve the collecting societies’ performance, introducing a new key performance indicator. This turning point is made possible by digital transformation and regulatory change. In the IPR industry, copyright holders’ performance has never been calculated, so the distribution of copyright revenues was based on the criteria approved by governance bodies/management.Originality/value>In the study, the authors demonstrate that digital transformation is able to enhance the intellectual capital of IPR-intensive companies introducing new ways to manage intangible assets and to measure performance.

The paper explores the aspects of formation, valuation and developmental resource of intangible assets in trade amid the growing role of online sales channels. The existing criteria of categorising the resources of trade companies as intangible assets are analysed with a focus on their suitability for the established practices. The structure of intangible assets is analysed for online and offline trade. The relevant types of intangible assets are identified and valuation problems are described.

The study provides detailed information about the cryptocurrency market as an IFRS object and indicates the methods of their accounting and their features. Data on the change in the total market capitalization of cryptocurrencies are shown, and the reasons for which they went into decline are revealed. Companies that may be interested in accounting for cryptocurrencies under IFRS are considered, as well as the official guidance of the IASB on the issue of accounting and reporting of cryptocurrencies, issued several years ago, is analyzed. Two standards IAS 38 \"Intangible Assets\" and IAS 2 \"Inventories\" are analyzed and the reasons why for which the company's cryptocurrency is mainly accounted for either as part of intangible assets or as part of inventories. The foreign experience of some companies that reflect the cryptocurrency according to IFRS is studied, as well as Azerbaijan's practice in this area is considered. Accounting standards have not yet been fully developed, as cryptocurrency has different characteristics from traditional financial assets. Therefore, businesses may experience uncertainty regarding the accounting of cryptocurrency. It is important for businesses to maintain proper accounting records regarding cryptocurrency. These records help businesses meet their tax obligations related to the purchase, sale and exchange of cryptocurrency. However, it can be difficult to find staff with adequate knowledge of accounting and recording cryptocurrency.

For a smart city, soft or non-physical assets share an important capital component with many impacts in different contexts. They enable a city to deliver and mainstream a people-centered policy in addition to the benefits provided by traditional, hard infrastructure. Soft assets can involve social and human capital, knowledge, participation, and innovative approaches that drive value in the city. However, it is always a challenge for city policy makers to identify and strengthen these soft assets using a systemic approach due to their inherent characteristics. This paper argues that soft assets should be strategically integrated into the development process of smart and resilient cities. Therefore, exploring various approaches to prioritize soft asset consideration would provide helpful guidelines to city policy makers for municipal value creation, and identify where the greatest needs for soft or intangible assets lie. This paper examines how to identify and decide which soft assets should take priority in smart and resilient cities. The findings can assist policy makers in their consideration of an optimal mix and balance of soft assets required in the city to improve living structures for a people-centered approach.

Despite the existence of a variety of conceptual approaches to rural development, there is a lack of methods that take into account intangible assets, such as, for example, social capital, leadership, and local identity. A more effective design of the rural development strategy may be achieved by uncovering knowledge regarding the manifestation of various intangible resources. Territorial development policies, both in terms of the level of socio-economic development and the presence of intangible resources in rural areas, are investigated in this study. The main objective is to determine how intangible resources manifest in specific empirical models of development policy for rural settlements. A novel ensemble of indices and indicators of socio-economic development and the manifestation of intangible resources, calculated based on the method of analytical hierarchies and frequency analysis, are provided. These allow for a comprehensive study of the development of rural areas by clustering settlements with a similar level of development. Patterns and deficits of resources in rural settlements are analysed according to empirical models. Verification of the empirical models is carried out by assessing the level of socio-economic development and indicators of intangible resources for 12 rural settlements in the south of Russia. Therefore, several groups of factors of intangible resources splitting the factors related (reflect the current state) and unrelated (reflect the development potential) to the socio-economic development of rural settlements have been specified.

Supply chain management systems (SCMS) championed by network leaders in their supplier networks are now ubiquitous. While prior studies have examined the benefits to network leaders from these systems, little attention has been paid to the benefits to supplier firms. This study draws from organizational theories of learning and action and transaction cost theory to propose a model relating suppliers' use of SCMS to benefits. It proposes that two patterns of SCMS use by suppliers-exploitation and exploration-create contexts for suppliers to make relationship-specific investments in business processes and domain knowledge. These, in turn, enable suppliers to both create value and retain a portion of the value created by the use of these systems in interfirm relationships. Data from 131 suppliers using an SCMS implemented by one large retailer support hypotheses that relationship-specific intangible investments play a mediating role linking SCMS use to benefits. Evidence that patterns of information technology use are significant determinants of relationship-specific investments in business processes and domain expertise provides a finer-grained explanation of the logic of IT-enabled electronic integration. The results support the vendors-to-partners thesis that IT deployments in supply chains lead to closer buyer-supplier relationships (Bakos and Brynjyolfsson 1993). The results also suggest the complementarity of the transaction-cost and resource-based views, elaborating the logic by which specialized assets can also be strategic assets.

PurposeThe purpose of the work is to solve the set problem and to study the competition and perspectives of division of labor of humans and machines during creation of intangible assets in Industry 4.0.Design/methodology/approachThe research is performed with the help of regression and comparative analysis by building regression curves and with the help of the qualitative structural and logical analysis.FindingsThe authors perform an overview of the factors that determine the advantages and limits of participation in creation of intangible assets in Industry 4.0, determine the perspectives and compile recommendations for division of human and machine labor during creation of intangible assets in Industry 4.0.Originality/valueThe results of the performed research confirmed the general hypothesis that machine technologies allow improving the innovative, marketing and organizational and managerial activities and activities in the sphere of R&D through automatization of certain stages of the process of creation of intangible assets. The authors determine the factors that define the contribution of machine technologies in this process and their competitive advantages as compared to human intellectual capital during creation of intangible assets. These advantages prove the possibility and expedience of division of human and machine labor during creation of intangible assets.