Search results

The purpose of this paper is to provide a cross-platform recommendation system that recommends the most suitable public Instagram accounts to Facebook users.

We collect data from both Facebook and Instagram and then propose a similarity matching mechanism for recommending the most appropriate Instagram accounts to Facebook users. By removing the data disparity between the two heterogeneous platforms and integrating them, the system is able to make more accurate recommendations.

The results show that the method proposed in this paper can recommend suitable public Instagram accounts to Facebook users with very high accuracy.

To the best of the authors’ knowledge, this is the first study to propose a recommender system to recommend Instagram public accounts to Facebook users. Second, our proposed method can integrate heterogeneous data from two different platforms to generate collaborative recommendations. Furthermore, our cross-platform system reveals an innovative concept of how multiple platforms can promote their respective platforms in a unified, cooperative and collaborative manner.

This work focuses on the interoperability of the blockchain from the viewpoint of its technological evolution in the wider context of supply chain systems. Interoperability concerns the most since it is among the most persevering problems in the process of blockchain adaptation. The study aims to trace and pinpoint all the different methods that affect the interoperability of blockchains, gather all the obtainable evidence and recognize gaps in between the applicable approaches mentioned across the contemporary academic literature.

An analysis is done of seven interoperability approaches based on their relevance, practical usefulness and adoption processes concerning the blockchain. Mainly, this work examines interoperability from several different perspectives. An interoperability modular decomposition via a layered model has been defined through the level of conceptual interoperability (LCIM) and level of information system interoperability (LISI), which represent the most popular metrics with regard to assessing the level of interoperability from a qualitative level.

Generally, the findings of this work are directed in two major aspects: Firstly, it expands the research around blockchain technology interoperability by providing crucial background information and pinpointing important connotations for both industrial and academic environments. It also defines and analyzes several different approaches toward the blockchain platform's interoperability. Secondly, it also identifies and proposes several scenarios that take advantage of multiple blockchain application approaches, highlights various issues and challenges to the evolution of interoperability standards and solutions and indicates the desired areas of further research.

An essential aspect of the originality of this paper is that, contrary to other work contributions, this work summarized the different interoperability approaches for blockchain in supply chain systems. Mainly, seven approaches were discussed for practitioners and researchers, and the open issues and future research direction were considered.

Social trading platforms are considered to be amongst the major innovations in online trading. The purpose of this article is to analyze the trading activity of traders on social trading networks by taking a behavioral approach. Additionally, the authors investigate the factors that influence the irrational part of trading activity derived from the key characteristics of these platforms, i.e. those dealing with social interaction.

The investigation utilizes an extensive set of trading data from two major platforms in Germany to study the trading behavior. The authors apply a fixed effects two-stage least squares (2SLS) approach to quantify the relationship between trading activity and performance and define overconfidence as the part of trading activity that is irrationally motivated and results in negative returns.

The results provide evidence for the negative relationship between overconfidence and return on social trading platforms. The authors find that the number of followers and some platform-specific features significantly affect the trading behavior of the traders.

The authors contribute to the existing literature by exploring how the novel social interaction characteristics of online trading impact trading activity by giving rise to a new dimension of overconfidence. In addition, the authors evidence that the different frameworks of the platforms motivate heterogenous behavioral responses by the signalers. Finally, the authors refine existing studies by applying a distinct methodology for modeling overconfidence.

Rolling bearings are basic mechanical elements for supporting rotational and reciprocating motion in engineering products. Many approaches have been proposed by researchers in order to facilitate the procedure of bearing design, but mainly concentrating on the development of PC‐based systems or relative software packages.The authors present a novel approach to implementing a design support system for rolling bearings based on the World Wide Web so as to achieve agility in rolling bearing design. The system was developed based on the philosophy of agile manufacturing by integrating various information resources, artificial intelligence, and Web technology with expertise. This Web‐based distributed system will be globally accessible by the user on the Internet and can be automatically sized according to the demand of application requirements. The system implementation issues are discussed in detail in this paper.

The digital platform economy has wide-ranging implications for the nature of work in the twenty-first century. The ease at which suppliers and demanders of labour come together across digital platforms creates a very new kind of labour market characterized by hyper-flexibility and an ambiguous employment relationship. Platform work has been hailed as providing employment opportunities for young people entering the labour market and other groups for whom access to more traditional forms of work is compromised (e.g. women with caring responsibilities or people with chronic health issues), or simply those seeking easily accessible, flexible work (e.g. students). On the other hand, unions and grassroots activist campaigners have highlighted the poor conditions that shape the experience of platform work, such as low pay, lack of choice over working time, tight control over the labour process and a dependency on platforms that belies their self-employed status. These dimensions of decent work are examined in the context of France and the United Kingdom, two countries which represent very different employment contexts (Milner, 2015), and thus provide insights into how specific country contexts may mediate the experience of platform work and the policy response.

This paper focuses on decision making related to the use of strategic inventory allocation in product platform design. The purpose of the paper is to present a novel approach to managing product variety by considering product and manufacturing strategy, and considering the supply chain benefits.

Discrete event simulation is used for analyzing product platform performance in terms of inventory level and throughput. Simulation parameters such as lead times and safety stock allocation are optimized by using an analytical model of strategic safety stock allocation.

The results show that strategic safety stock allocation supports product platform strategy by increasing production output, and reducing inventory level and customer order queues at a higher level of product variety.

Linking the safety stock allocation and product platform strategy facilitates simultaneous product and process design by providing the most optimum platform strategy at minimum safety stock allocation.

Strategic safety stock allocation facilitates decision making with regard to lean strategy by reducing inventory level, agile strategy by increasing the amount of product variety and outputs, and responsiveness by reducing the number of customer order queues.

The paper presents an innovative customer order decoupling point decision.

Technological advancements have catalyzed disruption in the banking sector. The impact of the metaverse on the banking sector is no exception. In view of this, the current paper aims to provide valuable insights into four key areas (i.e. corporate banking, retail banking, banking employees and public policy) that the metaverse could significantly disrupt.

Insights into four key areas of the banking sector that the metaverse could significantly impact were gathered from various invited contributors.

The invited contributors first introduce the association between their respective key areas with the metaverse. Subsequently, the opportunities and challenges relevant to the key areas were identified. Finally, future research agendas were proposed for the attention of all relevant stakeholders.

The metaverse's impact on key areas of the banking sector is discussed in this paper. Following the metaverse's potentially wide application in the banking sector, insights from the invited contributions offer great value to the relevant stakeholders.

The purpose of this paper is to highlight the drivers, barriers, benefits and risks affecting the integration of Internet of Things (IoT) into the e-government and to provide a future research agenda.

Existing literature examining the relationships between e-government and IoT is scanned and evaluated by conceptualizing the IoT concept in the e-government perspective.

The study shows that there are drivers to integrate IoT in e-government, such as ensuring the economy, efficiency and effectiveness of government operations, which would largely establish a relationship between the government and the citizens. Furthermore, there are barriers to such integration, given the lack of political will, the appropriate information technology infrastructure, the training of the stakeholders with a focus on the employee and the like.

The integration of IoT in e-government is a novel and weakly explored concept, particularly in the light of new advances such as blockchain in the e-government, which requires further exploration and conceptualization, thereby achieving a shared/common vision and body of knowledge for its further successful and sustainable adoption – to the best of the authors’ knowledge, the current study is one of these initial attempts.

Digital transformation has been changing the economic environment of enterprises in recent years. To remain competitive, they rely on an extensible software architecture, flexible workflow execution, and automated decision management. The concepts of service-oriented architectures (SOA), business process management (BPM), and business rules management (BRM) provide an adequate, yet isolated means of addressing many of these requirements. The paper aims to discuss these issues.

This study adapts from established research frameworks to structure the current state of research on the integration of SOA, BPM and BRM. The authors highlight the current research scope, point to disregarded topics and sketch out multidisciplinary research approaches.

While the three concepts are often discussed only in isolation or pairwise, approaches that integrate them are scarce. Against this backdrop, this study defines three types of research opportunities and identifies several directions for future research that should be explored from a technological as well as organizational perspective. Given the breadth of open questions, the authors present sources for each area of our research framework, which can serve as starting points for future investigations.

Except for well-established support for separate tasks and technologies, there is a lack of integrated standards, methods and platforms, which for example enable integrated decision-making across BPM and SOA.

Our contribution builds on established frameworks and clearly shows that the discussion on the integration of SOA, BPM and BRM cannot yet be regarded as sufficient. The research agenda highlights which areas explicitly benefit from a more precise consideration.

Discusses the implementation of engineering data management (EDM) which is one of the more recent technologies to be considered by enterprises needing to be more responsive to business pressures. Highlights the considerations for a successful implementation stressing the need for companies to learn from the mistakes and success of others. Only a timely and efficient implementation will realize the benefits of EDM.