Abstract

The purpose of this paper is twofold: (i) to investigate some of the main issues surrounding the classification of digital currencies, and (ii) to identify the accounting practices and standards tied to digital currencies. This paper discusses two different types of digital currencies, including: central bank digital currencies (CBDCs) and privately issued cryptocurrencies such as Bitcoin. The findings of this study suggest that current accounting standards do not precisely cover the accounting treatment of digital currencies, even though the estimated value of market capitalisation of cryptocurrency in 2022 was USD 200 billion. This conceptual paper identifies the imminent need for an accounting standard to provide guidance on the identification, classification, measurement, and presentation of digital currencies. In the interim, existing accounting standards can be amended to incorporate digital currencies to avoid inconsistent global accounting approaches.

Introduction

Digital currency is an unparalleled technological advancement that has received increasing attention from researchers, investors, financial institutions and regulators. It is a mode of exchange that does not have a physical or tangible basis and exists purely in an electronic form. It should not, however, be confused with electronic money such as an online bank account, which shows the amount of cash that is held in a specified account and is linked to a physical currency. Many businesses are now pursuing digital currency as part of their wider financial management system, and this should be appropriately recorded in their financial statements. Despite the rapid increase in the amount and frequency of digital currency transactions, there is no clear guidance from the International Accounting Standards Board (IASB). The classification of digital currencies is a significant issue, and lack of guidance from standard-setters affects the accounting treatment of digital currencies and disclosures in financial statements.

Current literature shows the lack of focus on accounting treatment of digital currencies. In this conceptual paper, we aim to address this literature gap by examining accounting classification and treatment of transactions involving digital currencies. In addition, the paper aims to discuss a number of potential risks associated with the use of digital currencies and lack of clear classifications. Key questions around the classification, reporting and disclosure of digital currencies are addressed in this paper, including: In what asset class should digital currencies be classified as? and, is there an existing accounting standard for digital currency within the current IFRS standards?

Summary and conclusion

Digital currencies represent a genuinely new development in the landscape of financial payments. The main issue is that there are currently no clear or universal accounting standards or classifications for digital currencies. It is critical that blockchain technology, regarded as the underlying technology of most digital currencies, is fully understood, in order to be able to create relevant accounting and taxation standards as well as regulatory frameworks. Blockchain could therefore positively impact business models due to its unique characteristics, which address a number of key business issues. In addition, it offers the possibility of ‘triple-entry accounting’, in which accounting entries are cryptographically sealed by a third entry and made accessible to all third parties. Furthermore, blockchain accounting can reduce errors in disclosure and earnings management, improve the reliability and timelines of accounting information, and accordingly mitigate information asymmetry.

Accounting standard setters seem to be struggling to cope with the exponential growth in digital assets, which has led to a lack of consensus among them about how to treat these assets. This demonstrates that there is an urgent need for clear guidance to be issued by the standard-setters, as this absence has hindered the development of a universal accounting practice for digital currencies and has thus posed a number of challenges for authorities in relation to the classification and measurement of digital currencies.

Abstract

The Internet of Things (IoT) is becoming pervasive and with each new installation of IoT platforms new and legacy brokers have to be exploited. New internal brokers are those under the control of the platform, while legacy external brokers are those in place managed by third parties. The solution proposed addressed problems of (a) interoperability to reduce set up time to cope with unknown data structures (devices, entities) distributed via brokers; (b) performance by dimensioning both front-end and back-end processes to reach high rates in a broker-based platform, while preserving full capability features of the data warehouse. Interoperability aspects have been addressed by introducing our concepts and a reasoner into an IoT Directory tool to manage Internal and External brokers, automate device discovery and registration from both standard and customized data models. Despite the managed complexity, a broker-based solution turned out to provide high performance. To this end, a specific assessment and architecture tuning have been performed and reported in the paper to give evidence and validation. The proposed integrated IoT Directory has been developed in the context of the Herit-Data Project, and it is currently used in the whole Snap4City network of 18 tenants and billions of data. Snap4City is an open-source IoT platform for Smart Cities and Industry 4.0, which is an official FIWARE platform and solution, EOSC service and libs of Node-RED.

Introduction

The Internet of Things (IoT) defined a paradigm for the computation and communication amongst things, which is becoming every day more and more pervasive and adopted in many different domains [1,2]. It is partially due to the worldwide intense deployment campaign about Low-Power Wide Area Network technologies [3], as well as to many approaches and protocols for communications amongst devices (e.g., Message Queue Telemetry Transport or MQTT, Next Generation Service Interfaces or NGSI, Advanced Message Queuing Protocol or AMQP, Constrained Application Protocol or COAP). The approach is also covering the cloud and fog infrastructures [4,5]. Thus, IoT network infrastructures are becoming every day more complex to be managed due to the networks’ structure and existence of several protocols, formats, and concepts [1,6]. Hence, the complexity is growing in terms of data management, not only for huge amount of data but also for interoperability and abstraction levels needed to data managing. Relevant aspects to be considered are security and privacy [7] on specific data models and entities. To increase the complexity, there is a range of different owners and managers who may control different parts of such IoT networks [8].

In this context, the concept of Gateway is relevant for any segments of IoT networks connecting, as well as for the Web of Things, WoT [9]. Gateways may be integrated with one or more Brokers to send/receive data to/from Devices/entities. The Gateways and Brokers are typically compliant with a single protocol and may be managed by third parties with respect to data management platform. In some cases, they are provided as public services for several interested customers in the same area (for example: Proximus for LoraWAN services [10]). A Gateway may abstract from the IoT Broker level managing multiple brokers for multiple organizations/tenants (which can be regarded as customers of Gateway services to manage several Devices), via some API and/or Web user interface. Typical IoT Brokers can only manage one organization, and thus are single tenant, meaning they broker messages using topic/entity concepts (which can be regarded as the key for subscription on that specific device/entity) without any internal partition of services, but as a sort of family of devices and subscriptions. Some IoT Brokers can be multi-tenant, such as the FIWARE Orion Broker [11,12], which provides support for partitioning the served devices/entities/topics in groups, and each of them may have a dedicated service/path for a specific scope (or a specific customer). Furthermore, devices of different tenants could exist physically in different places (even having identical identifiers, IDs), and the subscription to the broker’s tenant may imply receiving all messages/services in the partition in push. That is feasible only if the subscriber knows the service/path identifier and, in the event of access control, the subscriber has the grant to access the broker’s services. Different IoT Devices connected to the same broker adopt the same protocol, may use different data structures/models and have the same semantic information.

Conclusions

The proliferation of IoT devices, brokers, networks, data models, operators and tenants, makes the harmonization and management of IoT Platform a hard goal. This paper offers an analysis and a comparison amongst relevant existing platforms, and it points out the basic requirements to achieve such aims. These identified requirements are in most cases not addressed by main platforms which prefer to stay on their own end-to-end solutions with limited interoperability and capacity of exploiting legacy IoT networks in place, in terms of performance. The proposed solution addressed problems of (a) interoperability by reducing set up time to efficiently detect and learn how to process unknown data structures (devices, entities) distributed via brokers; (b) performance by dimensioning the front-end and back-end processes to reach high rates in a broker-based platform, while preserving full capabilities features of data warehouse.

As to interoperability, the main identified and solved problems are those related to a large variety of Data Models coming from non-controllable External Brokers. The issue has been solved by designing and implementing a harvester and reasoner that is capable to automatically recognize/understand and map the new data models/types into those already known by Knowledge Base. This approach, together with the definition of a comprehensive meta model and dictionary, has allowed to speed up the process more than 800 times. The harvesting and comprehension process can be periodically performed to keep the platform updated with any newly defined data models by third party brokers. Furthermore, the process is helped by Km4City ontology and Data Dictionary to recognize the new data types and models according to the semantic domain.

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.

Abstract

Keywords

References

Abstract

The diffusion of e-commerce has played a significant role in recent rural economic development in China. E-commerce is also considered as an efficient channel to alleviate poverty in rural China. Voluminous studies have investigated the contribution of e-commerce to agricultural development, yet it is lacking empirical evidence as to the effects of e-commerce on rural poverty alleviation. Since the year of 2014, in order to develop rural e-commerce, Chinese government launched the National Rural E-commerce Comprehensive Demonstration Project. This gradual involvement policy offered a natural experiment for evaluation of e-commerce. Based on village-level survey data from rural China and Heckit method, our study finds that rural e-commerce has a significantly positive effect on rural income. Moreover, the effect is inverted U-shaped for the relative-poverty villages. The estimation of the propensity scores matching model confirms that the results are robust. The following policy recommendations are proposed: (1) policy support to rural e-commerce should prioritize the poverty-stricken villages. By doing so, the marginal income effects of e-commerce will be maximized. (2) Investment in internet infrastructure and establishment of human resources for e-commerce in rural areas will have spillover effects, increasing rural income through the “digital dividend”.

1. Introduction

Since 1978, China has lifted more than 700 million people out of poverty. China was the first developing country that achieved the Millennium Development Goal for poverty alleviation set by the United Nations (Liu et al. 2019). Although the Chinese government has prioritized policies that target at improving rural residents’ welfare, poverty remains a critical problem with 16.6 million people estimated to live in poverty and an poverty incidence rate of 1.7% in 2018 (NBSC 2019). Poverty alleviation remains a massive task for the Chinese government, which is determined to eradicate absolute poverty by 2020.

Thanks to the development of information technology and increasing use of smartphones in rural areas, e-commerce penetration in the rural economy has been on the rise in recent years. Rural e-commerce is a direct approach to take advantage of information technology and achieve higher profits. It adapts to the requirements of rural industrial transformation and upgrade. By doing so, it provides new drivers for the revitalization of rural industry. In recent years, “empowerment” to players of rural e-commerce has also attracted much attention (Ogutu et al. 2014; Leong et al. 2016; Zeng et al. 2018). In these literature, rural e-commerce was considered as an efficient tool to enable people to develop modern agriculture and commerce. Especially, e-commerce promoted agricultural value chain development and commodity circulation (Baorakis et al. 2002; Mintert 2003; Jalali et al. 2011; Parker et al. 2016; Song et al. 2019). E-commerce, unlike traditional commerce in which employees need to be present in stores, enables its staff to work from home. It is a highly accessible form of offfarm work for those constrained in rural areas due to either agricultural production or caring responsibilities. In some rural areas, e-commerce has become a potential engine for farmers’ income growth. As an innovative solution, poverty alleviation through e-commerce began to emerge.

In the last fifteen years, marketing channel options such as social media, search engines, and price comparison sites have supplemented traditional marketing channels such as sponsoring, print advertising, events and TV commercials (Dholakia et al., 2005; Rangaswamy and Van Bruggen, 2005). This change has led to new types of combinations, and the traditional way of doing business and marketing within the retail sector has met new forms of competition. Indeed, when product features are easily copied, and production costs and margins are constantly under pressure, it is said that well managed and sound multi-channels are a source of competitive edge – to stand out from the rest (Payne and Frow, 2004; Rodríguez-Díaz and Espino-Rodríguez, 2006; Rosenbloom, 2007; Sharma and Mehrotra, 2007). Keeping pace with the advent of the Internet and e-commerce, streams of research have devoted efforts to investigating, for example, the optimal blend of online and offline channels (Friedman and Furey, 1999; Kumar and Venkatesan, 2005; Rosenbloom, 2007), and how the addition of online channels might offer extra edge to, or hinder, firm performance (Cheng et al., 2007; Webb and Lambe, 2007). Furthermore, the performance implications of retailing online versus offline, as well as differences between generalists and specialist retailers, have been examined thoroughly (Min and Wolfinbarger, 2005). Nevertheless, we believe that the present literature on the link between retailers’ strategy, retail format and its marketing channels is somewhat dated (e.g. Kabadayi et al., 2007; Vorhies and Morgan, 2003), and as a consequence the dramatic change in the retail sector towards e-commerce and the use of online marketing channels has not been particularly well captured. Grewal et al. (2004) find no evidence that we can easily apply research on offline retailers to guide online retailing, and we argue that there are still very few studies made after the breakthrough of e-commerce that explore the performance implications of matching (or mis-matching) the multi-channel setup to retailers’ strategy and retail format. This article aims at addressing this gap by applying a configurational approach (Fiss, 2007; Miller, 1996) to fit between important design elements for a retailer. In the article, we develop, and empirically test, viable and less viable combinations of business strategy, retail format and multi-channel setup and how they affect the financial performance of retailers (profit and growth).

Stock Exchange Markets provide a service to trade stocks and bonds. They have multiple roles in the economy [?] such as raising capital for companies, government capital raising for development projects and mobilizing savings for investment. Additionally, it is an indication of the general trend in the economy for a particular country. For many years, stock exchanges were physical locations where buyers and sellers met and negotiated. With the improvement in communication technology in the late 20th century, traders started to transact from remote locations in what became known as electronic trading (etrading). There are clear indications attest that the electronic crime threat in stock markets is an increasing threat, with the possibility of significant costs [3,4]. Therefore, implementing an effective information security measures and controls has become a critical success factor for all parties (regulators, brokerage companies and individual investors) to ensure a safe environment for electronic trading. Hereby, a threat modeling has to be developed and be followed for optimizing environment security. Threat modeling is a method for improving security by identifying assets that needs protection and weaknesses. Then defining actions reduce the effects of threats to the system. In stock exchange environment, the web servers are companies assents that need a protection. Digital Certificate is one of the technologies required to maintain the protection. It is based on Secure Socket Layer (SSL) [6] and Transport Layer Security (TLS) [8] protocols. SSL/TLS protocols are considered the de facto standard for providing secure communication over the Internet. The protocols have evolved over years to fix the weaknesses and drawbacks detected, add protection against discovered attacks and support new cryptographic algorithms that were defined. Several security assessments should be conducted to make sure that stock exchange markets are aligned with recent cyber threats. Moreover, companies should evaluate their systems and implemented technologies to identify any weakness. Then take actions toward enhancing the protection of their clients’ information. The rest of this paper is organized as following. Section 2 demonstrate the previous studies related to cyber threats in stock exchange. Followed by Sect. 3 which define the threat modeling for this environment. Section 4 introduce SSL/TLS protocols background, the known attacks and deployment best practices. The case study is presented in Sect. 5. The security assessment, its results and discussion are presented in Sect. 6. The conclusion is presented in Sect. 7 along with future work.

International Conference on Communication, Management and Information Technology

اقتصاد مدرن نه تنها بر اساس منابع انسانی و سرمایه قرار دارد بلکه مهم تر از همه دارای اطلاعات تشکیلات اقتصادی است . اطلاعات صحیح در زمان صحیح تعیین کننده پیشرفت و موقعیت رقابتی یک تشکل اقتصادی در بازار است ، در حالیکه فقدان این اطلاعات حتی ممکن است منجر به شکست آن تشکل شود . ابزار و استراتژی تجارت الکترونیک توسعه یافته ی صحیح که به درستی برای ویژگی های این نوع از تجارت ایجاد شده و مورد استفاده قرار گرفته اند ، اثر مثبتی بر موفقیت یک تشکل اقتصادی دارند . هدف این مقاله نشان دادن ابزار مدرن و مورد استفاده در تجارت الکترونیک ، از نظر افزایش پوشش و فروش محصولات و خدمات مختلف ، با توجه ویژه به شناخت یک نام (برند) تجاری خاص می باشد . نویسندگان برای ارائه ی راه حل های مدل تجاری از یک سرویس انتخاب شده و ارائه شده توسط تجارت الکترونیک که یک راهنمای لهستانی در نرم افزار فروشگاه الکتورنیکی است تلاش می کنند ، هم چنین به منظور ارائه ی منابعی از روش های خوبی که چگونگی ارائه ی سرویس ها با روش مطلوب و با استفاده از ارتباطات IT را تعریف می کنند ، تلاش می کنند .

مقدمه
اصطلاح تجارت الکترونیک به معنای یک روش مدیریت تجاری با استفاده از ارتباطات IT و به طور عمده برنامه های کامپیوتری است . تجارت الکترونیک در میان چیزهای دیگر به ارسال مدارک ، تبادل داده میان یک تولید کننده ، توزیع کننده و شریک تجاری ، جلب مشتری های جدید ، بازارهای غالب و برگزاری تله کنفرانس ها اشاره دارد . تجارت الکترونیک شامل موارد زیر می شود :
– تجارت الکترونیکی
– شرکت الکترونیکی
– اقتصاد الکترونیکی
– جامعه ی الکترونیکی
– دولت الکترونیکی
– بانکداری الکترونیکی
– آموزش الکترونیکی