Abstract

     In hacker communities, tech-savvy pioneers collect and share information on nascent technologies. The pool of information shared among users reduces uncertainty about digital technology, but, first and foremost, it reveals entrepreneurial opportunities to users in the community, which is a central tenet of innovation commons theory. In this paper, we are first to explore the role of local hackerspaces for digital entrepreneurship in German counties using cross-sectional time series data. We find that longer-lasting hackerspaces are strongly correlated with the level of digital entrepreneurship in regions, particularly in agglomerations and urban contexts.

Motivation

     Hackerspaces are “community-operated physical places, where people share their interest in tinkering with technology, meet and work on their projects, and learn from each other” (Hackerspace.org, 2021). This definition encompasses a variety of third places of similar nature in terms of their characteristics and external features (van Holm, 2014), such as hacklabs (Maxigas, 2012), makerspaces (Smith et al., 2013, Hatch, 2014, van Holm, 2017), and fablabs (Gershenfeld, 2005, Walter-Herrmann and Büching, 2013). Hackerspaces bring together communities of tech-savvy users around the use of nascent technologies, “engaging them in collective action and developing rules to generate, share and govern innovation resources” (Cohendet et al., 2021 p. 2). A growing number of hackerspaces have been founded worldwide (Guimarães Pereira et al., 2017) and there is an ongoing debate about their economic significance (Anderson, 2012, Williams and Hall, 2015, van Holm, 2017, Svensson and Hartmann, 2018, Boutillier et al., 2020), in particular with regard to their impact on entrepreneurship (Mortara and Parisot, 2016). The relevance of hackerspaces for innovation and regional development is supported by anecdotes from Silicon Valley, where many successful entrepreneurs were born out of hackerspace environments.2

Conclusion

     In this paper, we are first to explore and provide quantitative evidence for a weak positive correlation between hackerspaces and digital entrepreneurship in regions. In a series of fixed-effect Poisson panel models, we find that the existence of a hackerspace can help explain some of the variation in start-up rates observed between 2001 and 2014. The longer a local hackerspace exists, the higher is the digital start-up rate as measured by the annual number of newly founded firms per civilian worker. Results continue to hold once we correct for some of the plausible treatment selection and omitted variable bias in our data using propensity score matching methods, as hackerspaces are not randomly assigned to regions but are more likely to emerge from larger population of tech-savvy users and aspiring entrepreneurs.

     Still, tentative findings point to the great importance of hackerspaces as a prime example of innovation commons structures and, potentially, a novel explanation for new firm formation in regions. Hackerspaces as supporting facilities help generate and reveal valuable, complementary information on nascent technology and entrepreneurial opportunities that is otherwise dispersed and privately held by users. With more empirical research on the horizon, a new generation of regional and entrepreneurial policies might also want to consider the support of hackerspaces. This could potentially bring in an alternative set of innovation agents in the ‘middleground’, previously not accounted for by most policies. The findings of this paper suggest that hackerspaces, at least in urban contexts, have been instrumental in fostering digital entrepreneurship in Germany and expanding the range of commercial opportunities.

Abstract

     Human cognitive time has become a key asset of the digital economy, yet we lack the means to manage it. In response to that need, we propose a technology to manage cognitive time in economic organizations. This technology is called cognitive time-driven activity-based costing (CTABC), and it extends the established time-driven activity-based costing technology. CTABC accounts for human agents’ cognitive time and the fact that cognitive time typically does not equal physical clock time for a given economic activity. CTABC also unearths a hidden lever effect that leads to considerable economic inefficiencies. An illustration of the proposed CTABC shows the limitations of contemporary approaches to cost assessments, which ignore errors caused by workers’ cognitive time estimation. This paper contributes to the literature on cost accounting technology and the future of the digital economy. Specifically, it enriches the literature on the problem of the accuracy of employees’ time estimates.

Introduction

     “In an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.”

     In today’s competitive business environment, cost accounting systems must provide accurate information to managers so that they can make well-grounded decisions without negative impacts on the quality of products and services (Ganorkar et al., 2020; Hardan and Shatnawi, 2013; Zamrud and Abu, 2020). Without accurate cost accounting, managers cannot balance incomes and costs to sustain the endeavors of projects and govern organizations, firms, and even whole economies (Berisha, 2017; Ganorkar et al., 2020; Hardan and Shatnawi, 2013). Cost management is crucial for both for-profit and not-for-profit organizations that aim to be competitive and cost efficient (Hofmann and McSwain, 2013; Stouthuysen et al., 2014; Varila et al., 2007). Although the importance of cost accounting is beyond reasonable doubt, studies have shown that understanding cost structures and dynamics and cost assessments is not a trivial task for accountants and managers (Berisha, 2017; Hardan and Shatnawi, 2013; Uyar and Kuzey, 2016).

Discussion and conclusions

     In today’s highly competitive environment, there is an urgent need to calculate costs and revenues accurately so that companies can survive and ensure long-term profitability (Berisha, 2017; Ganorkar et al., 2020). Calculating the cost of products and services, however, remains a difficult exercise to ensure that costs do not exceed market prices. The TDABC model was proposed to remove the limitations of traditional costing systems and the ABC model. The distinctive feature of TDABC is that the time of an activity is at the forefront of the assessment of the cost of that activity. However, employees’ time estimates are prone to measurement errors in cost assessment (Barros and da Costa Ferreira, 2017; Cardinaels and Labro, 2008; Gervais et al., 2010). They lead to misinformed managerial decision making because TDABC accounts for only one kind of time, namely physical or clock-time, assuming that it is objective. The cognitive science literature shows a significant difference between a worker’s cognitive time and physical clock time, understood as the relationship between perceived time and physical time (Block and Eisler, 1999; Levin and Zakay, 1989). In this paper, we propose an updated version of TDABC that accounts for human agents’ cognitive time and the fact that cognitive time typically does not equal physical time, hence producing CTD. The CTABC technology proposed in this paper remedies the shortcomings of time assessment using traditional TDABC by accounting for CTD and incorporating it into the TDABC calculations.

Abstract

     The information age set off a revolution for organizations and institutions without precedent. Big production of data is a major competitive advantage for companies. Therefore, there are great economic incentives to monetize such data. However, there is evidence that indicates clear vulnerability in terms of user privacy, thereby setting a new paradigm in the search for a balance between privacy and security. This article offers a brief history of privacy to this day, deepens the scope and importance of its standardization in the regulation and future of digital markets.

The Right to Privacy in the Digital Age

     On December 18, 2013, the General Assembly of the United Nations approved the resolution entitled “The Right to Privacy in the Digital Age” for all people (United Nations 2017). This resolution establishes that indiscriminate global surveillance implies a serious violation of human rights and seeks to reaffirm the fundamental principles adopted in the Universal Declaration of Human Rights of 1948 (United Nations General Assembly 1948, article 12), the International Covenant on Civil and Political Rights (Joseph and Castan 2013, article 17), and the International Covenant on Economic, Social, and Cultural Rights (Saul, Kinley, and Mowbray 2014). In particular, this resolution makes it clear that “unlawful or arbitrary surveillance and/or interception of communications, as well as the unlawful or arbitrary collection of personal data, as highly intrusive acts, violate the right to privacy, can interfere with other human rights, including the right to freedom of expression and to hold opinions without interference, and the right to freedom of peaceful assembly and association, and may contradict the tenets of a democratic society.”

Conclusion

     The digital economy plays a fundamental role in the world economy and has been the subject of study by many academics and non-academics for some years. Its real impact on the growth of countries, although it could be incompletely and/or imprecisely measured, points to its growing importance as an engine of economic growth in the upcoming years. However, as it grows in importance, it also faces numerous threats that put its sustainability and functioning at risk, such as digital piracy, violation, and leakage of private data and cybersecurity.

     These threats, which in many cases affect the personal data of millions of users, require some regulation and protection that can establish operating guarantees in the future. Privacy seems to be a moving target and requires an international effort in order to set a common regulation that can enable economic development. Standardization turns out to be crucial and requires an ongoing commitment above any political or eventual issue.

1. Introduction

2. Global problems of shadow economy estimation methodologies: theoretical background

3. The statistics of shadow economy scope in Lithuania by different methodologies

4. The features of digital shadow economy

5. Conclusions

Funding

Reference

The article covers an extremely topical but hardly researched problem of digital shadow economy estimation. Thus far, the phenomenon of digital shadow economy has not been universally defined either by scientists or by institutions responsible for the combat with shadow economy. Traditional shadow economy is commonly estimated applying direct and indirect methods possessing their strengths and weaknesses. As a result, final estimations of shadow economies are rather variant. For instance, with reference to Schneider (2014), the scope of shadow economy in Lithuania achieved 27 per cent rate in 2014 whereas the figure estimated by Lithuanian Department of Statistics composed 15 per cent rate. It can be presumed that the divergence of the results has been determined by application of different shadow economy estimation methods. The interviews with the experts of shadow economy have revealed that although the volumes of e-trade and e-transactions are increasing, indicators of digital shadow are not still included in the estimations of shadow economy.

Introduction

Topicality of the problem. The phenomenon of digital shadow economy has been analysed in numerous scientific and information sources due to its specificity and depth of the problem. Thus far, the concept of shadow economy has not been precisely defined either in national or in international levels, which serves as the key reason for rather different scopes of shadow economy calculation and estimation. According to Zukauskas (2013), estimation of the real scopes of labour market shadow, as well as estimation of the other shadow economy activities, is complicated since shadow market operators are inclined to hide their activities. For the purpose to describe shadow economy and estimate its scopes, at least roughly, the variety of methods is engaged. Following the statistics, the figures of shadow economy in European countries are significantly different. The scopes of shadow economies in the countries of Central, Eastern and Southern Europe are considered to be the highest. Transfer of business activities to electronic space alongside with increasing volumes of e-trade determine the need to establish which share of shadow economy has been transferred to remote (electronic) platforms. The fact that the concept of shadow economy has not been universally defined in any official documents, proposes that this sphere has been insufficiently researched.

1. Introduction

2. Economic, ego and demographic determinants of subjects’ participation in digital shadow economy: theoretical background

3. The methodology of the empirical research

4. The results of the empirical research

5. Conclusions

Funding

References

This article is aimed at theoretical and empirical identification of economic and demographic characteristics of the subjects, operating in digital shadow economy. Although, in general sense, the characteristics of the subjects, operating in digital shadow economy, are not extremely different from the ones of the subjects, operating in traditional shadow economy, the expert evaluation has enabled to identify the distinctive features of an illegal digital market seller, who can be represented as a young or middle-aged male with higher education, a professional in his operational field. With reference to the research results, sellers in digital shadow economy include the entities with officially registered activities, who are trying to evade taxation of the revenues earned from the operations in e-space. On the other hand, according to the experts, the amount of the officially accounted revenue earned by these entities may reach up to 300 EUR. Hence, the defined profile of an illegal seller, as of a subject, operating in digital shadow economy, proposes that a seller in digital shadow economy is an intellectually developed person with advanced professional skills, but insufficient financial earnings.

Introduction

As argued by Wall (2005), the empowering of an individual to exploit networked technology to carry out incredibly complex and far-reaching tasks countless times globally is one of the most profound transformations of trade. With an attraction of opportunities, including easy availability, use and control of technologies (Ingram & Hinduja, 2008; Amasiatu & Shah, 2014; Camarero et al., 2014), variety of products and services on sale economy (Mikalajunas & Pabedinskaite, 2010; Sirkeci & Magnusdottir, 2011) low price (Mikalajunas & Pabedinskaite, 2010; Ho & Weinberg, 2011; Vida et al., 2012; Yu et al., 2015), time saving (Ho & Weinberg, 2011; Williams et al., 2010; Yu et al., 2015; Amasiatu & Shah, 2014 and others), convenient delivery terms (Vida et al., 2012; Sirkeci & Magnusdottir, 2011) and e-communication with a consumer (Mikalajunas & Pabedinskaite, 2010), more and more product buyers and service providers are entering the e-trade. Nevertheless, difference between corporate and personal, typical of e-environment (Calluzzo & Cante, 2004; Shang et al., 2008; Williams et al., 2010), in combination with the lack of public self-consciousness (Taylor, 2012; Arli et al., 2015; Amasiatu & Shah, 2014) determine subjects’ participation not only in formal, but also in digital shadow economy. Although the precise scopes of digital shadow economy have not still been estimated due to the lack of universally acceptable methodologies and difficulties to track all kinds of activities, one recent estimate of global corporate losses stands at around €750 billion per year (Europol, 2011).

1. Introduction

2. Digital shadow activity related terms and interpretations

3. The methodology of the empirical research

4. The results of the empirical research

5. Conclusions

References

The article covers a new topic in the sphere of digital shadow economy – consumers’ attitudes towards this phenomenon. Increasing transfer of transactions to electronic space determines the growth of the number of illegal digital operators and promotes consumers’ involvement in digital shadow trade. Scientific literature does not contain any universal definition of digital shadow economy. Hence, the variety of terms, interpretations and features relevant to this phenomenon is rather wide, which determines the necessity to define the precise concept of digital shadow economy from the point of view of consumers as active participants in this field. This article is aimed at definition of the concept of digital shadow economy from consumers’ position and identification of the measures would discourage potential consumers from participation in digital shadow economy. To increase the size of the survey sample, the method of “snowball” was engaged. The results of the research have revealed that consumers are inclined to distinguish criminal activities (drugs, prostitution, credential steals, etc.) from illegal economic activities, which also violate established legal norms and regulations. The participants of the survey perceive that the activities of digital shadow economy are performed exceptionally in electronic space without official registration of business and evading tax payment. Participation in digital shadow economy is voluntary and mutually beneficial to both transaction parties (a trader and a consumer). With reference to the results of consumers’ evaluation, definition of digital shadow activities as illegal ones, development of the efficient legal framework, containing clearly established criminal and/or administrative responsibility for a consumer as a party of digital shadow transaction, public announcement and availability of the information on illegal e-traders in e-space, availability of appropriate protection software, more intensive supervision and control, establishment of e-police department and assurance of the sufficient number of supervising officers can be considered the most efficient measures of digital shadow economy prevention.

Introduction

With reference to Petrovic – Lazarevic and Sohal (2004), e-business, which refers to the transactions conducted over computer networks, has been of considerable interest to practitioners and researchers primarily because of its influence on digital market participants. Removing numerous barriers (e.g. geographical, complex transaction, complicated payment, etc.) and ensuring the variety and availability of products and services on offer, an explosive growth of online business has provided a wealth of opportunities for consumers to become participants of digital shadow economy, i.e. obtain items and services from illegally operating online entrepreneurs (Dobson et al. 2015). Numerous social drivers such as the contrast between personal and corporate or low level of public selfconsciousness determine social acceptability of online purchases without making sure whether a supplier operates with complete legality or even realising the offensive nature of the activities. Thus far, the studies on the topic of digital shadow consumption have basically covered the analysis of the particular forms (e-fraud – Gregg, Scott, 2006; Blackledge, Coyle, 2010; Akintoye, Araoye, 2011; Vlachos et. al. 2011; Amasiatu and Shah, 2014 and others; digital piracy – Hill, 2007; Higgins, 2007; Williams et. al., 2010; Belleflamme, Peitz, 2010; Yoon, 2011; Camarero et. al.2014; Vida et. al. 2012; Taylor, 2012; Yu et. al., 2015 and others or social determinants (contrast between personal and corporate – Calluzzo, Cante, 2004; Shang et al., 2008; Williams et al., 2010; low level of public self-consciousness – Amasiatu, Shah, 2014; social bonding – Higgins et al. 2008; Yu et al., 2015; relativism – Arli et al., 2015) of this phenomenon. However, the concept of digital shadow economy from consumers’ point of view has hardly been researched. The research of consumers’ attitudes towards digital shadow economy is scientifically significant due to several reasons.

At the St. Petersburg International Economic Forum in June 2017, the President of the Russian Federation V.V. Putin proposed to launch a large-scale system program for the development of the economy of a new technological generation, the digital economy [1]. Presidential Decree No. 203 On the Strategy for the Development of the Information Society in the Russian Federation for 2017–2030 contains an official definition of this phenomenon: “the digital economy is an economic activity in which the key production factor is data in digital form, processing of large volumes and the use of analysis results that, in comparison with traditional forms of management, make it possible to significantly improve the efficiency of various types of production, technology, equipment, storage, sale, and delivery of commodities and services” [2]. Thus, the digital economy has become the main trend in the development of the modern information society, including e-government, industrialization 4.0, advanced financial technologies, and knowledge management. In the digital economy, quick access to information and knowledge can be seen as the main asset of an organization. Knowledge is the key asset of any organization, but Russian organizations are still at an early stage of understanding the importance of managing this valuable asset. Knowledge management is critical for the success of an organization in both the real and digital environments. Economic innovations are often a direct result of knowledge management and their exchange. Information technologies provide new opportunities for effective work and an even more effective exchange of knowledge. The purpose of this paper is to investigate the role of knowledge management in the processes of digital transformation.