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This study aims to determine the factors that encourage Indonesian banks to collaborate in the banking networks ATM Prima and ATM Bersama to achieve business efficiencies.

A combination of methods is used to collect both qualitative and quantitative data. Factor analysis and different testing technics are used. The data were obtained through interviews with managers of the banks involved in the two banking networks included in this study.

This research addresses ATM banking from three perspectives: banks that collaborate in ATM networks, banks that are joint ATM providers and banking customers that use ATMs. The results show that the banks in the study are more concerned about cost-effectiveness and cost-efficiencies in both the operational and investment aspects of supporting their ATM infrastructures. ATM providers place more importance on creating the most user-friendly, stable, wide-ranging and continuous system of services by collaborating with other banks in networks that provide ATM services. Customers put more importance on paying the minimum possible administration fees and the availability of specific banking services across a wide area.

This research took place over a period of only one year. This limited the depth of the data collected. A longer study using data that cover more than one fiscal year would have generated more detailed information.

This study places importance on maximizing cost-efficiencies to keep bank fees low for customers. There are significant investment and operational costs associated with setting up and operating ATMs and of adding and managing additional ATMs. This is particularly so in an era when their use is on the decline owing to the increasing use of electronic banking.

The social implications of ATM banking refer to the reduced administration fees customers pay as banks incur cost savings from collaborating on infrastructure and services. The availability of ATMs from specific banks could be replaced by one joint ATM machine that is situated in a specific area where electronic banking is not available. Banks’ customers tend to move to other banking services, and this means banks could lose a lot of their existing customers unless they can come up with unique services that are both accessible and user-friendly.

The originality of this research is that it recommends that some strategies Indonesian banks could use to become more efficient and effective, including forming ATM alliances to maximize efficiency and to achieve a competitive advantage.

Given that Blockchain technology poses a growing challenge to the banking industry, this paper aims to analyse the innovation of Blockchain banking with regard to its systemic dimension, as well as dynamics of competition. The empirical research demonstrates how the systemic characteristics of Blockchain banking relate to the pursuit of strategies and to what extent these strategies influence the directional path and level of technology diffusion.

The research study uses a case study methodology to explore the strategic competition of Blockchain banking. The study proposes the systemic innovation model for analysing and tracking the path of innovations. The model can be applied to any industry to understand the process of innovation development and the strategies to win market share in the banking industry. This research makes a contribution towards the theory of technology diffusion to understand the directional path of innovations.

The analyses of findings reveal the situation whereby most banks still compete to create their own Blockchain banking systems. The analyses, based on the systemic innovation model, also shows the low systemic feature of Blockchain banking at present. From the technology diffusion perspective, the future of Blockchain banking may need cross-chain interoperability to support a full spectrum of payments and value exchanges on the internet of things.

The main contribution of this paper is the systemic analysis of the latest innovation of Blockchain banking. Given that the research also includes the major banking innovation cases of ATM/cash cards, credit cards and electronic fund transfer at the point of sale/debit cards, the comparative analyses offer strategic insights to predict the progress, as well as pattern of technology development and diffusion for the case of Blockchain banking.

Expert profiling plays an important role in expert finding for collaborative innovation in research social networking platforms. Dynamic changes in scientific knowledge have posed significant challenges on expert profiling. Current approaches mostly rely on knowledge of other experts, contents of static web pages or their behavior and thus overlook the insight of big social data generated through crowdsourcing in research social networks and scientific data sources. In light of this deficiency, this research proposes a big data-based approach that harnesses collective intelligence of crowd in (research) social networking platforms and scientific databases for expert profiling.

A big data analytics approach which uses crowdsourcing is designed and developed for expert profiling. The proposed approach interconnects big data sources covering publication data, project data and data from social networks (i.e. posts, updates and endorsements collected through the crowdsourcing). Large volume of structured data representing scientific knowledge is available in Web of Science, Scopus, CNKI and ACM digital library; they are considered as publication data in this research context. Project data are located at the databases hosted by funding agencies. The authors follow the Map-Reduce strategy to extract real-time data from all these sources. Two main steps, features mining and profile consolidation (the details of which are outlined in the manuscript), are followed to generate comprehensive user profiles. The major tasks included in features mining are processing of big data sources to extract representational features of profiles, entity-profile generation and social-profile generation through crowd-opinion mining. At the profile consolidation, two profiles, namely, entity-profile and social-profile, are conflated.

(1) The integration of crowdsourcing techniques with big research data analytics has improved high graded relevance of the constructed profiles. (2) A system to construct experts’ profiles based on proposed methods has been incorporated into an operational system called ScholarMate (www.scholarmate.com).

One shortcoming is currently we have conducted experiments using sampling strategy. In the future we will perform controlled experiments of large scale and field tests to validate and comprehensively evaluate our design artifacts.

The business implication of this research work is that the developed methods and the system can be applied to streamline human capital management in organizations.

The proposed approach interconnects opinions of crowds on one’s expertise with corresponding expertise demonstrated in scientific knowledge bases to construct comprehensive profiles. This is a novel approach which alleviates problems associated with existing methods. The authors’ team has developed an expert profiling system operational in ScholarMate research social network (www.scholarmate.com), which is a professional research social network that connects people to research with the aim of “innovating smarter” and was launched in 2007.

The current air traffic management (ATM) operational approach is changing; “time” is now integrated as an additional fourth dimension on trajectories. This notion will impose on aircraft the compliance of accurate arrival times over designated checkpoints (CPs), called time windows (TWs). This paper aims to clarify the basic requirements and foundations for the practical implementation of this functional framework.

This paper reviews the operational deployment of 4D trajectories, by defining its relationship with other concepts and systems of the future ATM and communications, navigation and surveillance (CNS) context. This allows to establish the main tools that should be considered to ease the application of the 4D-trajectories approach. This paper appraises how 4D trajectories must be managed and planned (negotiation, synchronization, modification and verification processes). Then, based on the evolution of a simulated 4D trajectory, the necessary corrective measures by evaluating the degradation tolerances and conditions are described and introduced.

The proposed TWs model can control the time tolerance within less than 100 s along the passing CPs of a generic trajectory, which is in line with the expected future ATM time-performance requirements.

The main contribution of this work is the provision of a holistic vision of the systems and concepts that will be necessary to implement the new 4D-trajectory concept efficiently, thus enhancing performance. It also proposes tolerance windows for trajectory degradation, to understand both when an update is necessary and what are the conditions required for pilots and air traffic controllers to provide this update.

The purpose of this paper is to explore the development of a knowledge management (KM) strategy at the Central Bank of Nigeria (CBN) and how this was embedded in the business processes of the bank.

Literature research and a case study were used as the methodology of the paper.

The need to align KM strategy with business strategy was identified as critical to the success of KM. It was discovered that focusing KM on the Bank's payments system process helped create value and drive business results. A combined approach of codification and personalization was adopted for the KM program of CBN. The strategy adopted involved using a two‐pronged approach of communities of practice and a functional portal to drive knowledge management. The paper identifies that this strategy is adding value to the organization and increasing knowledge flows across a dispersed and distributed work environment.

Knowledge management in large public sector organizations in Africa is not common. Equally, KM in regulatory financial institutions like Central Banks in Africa is not very common. The paper highlights the challenges of implementing a KM program in a distributed, dispersed and networked public sector organization with 36 branches serving a population of 160 million people in sub‐Saharan Africa.

InfoMall is a program led by the Northeast Parallel Architectures Center featuring a partnership of approximately twenty‐four organizations with a plan for accelerating development of the High‐Performance Computing and Communications (HPCC) software and systems industry. HPCC is a critical technology where the United States has clear international leadership and which will have unprecedented impact on industry, education, society, and defense. The communications component of HPCC is critical to developing HPCC products. Acceptance of HPCC by these real‐world sectors has been delayed by the extremely hard problem of HPCC software development. InfoMall employs a novel technology development strategy involving closely linked programs in technology extraction and certification, software development, marketing, education, and training, economic development, and small business support. The process is constructured and explained by analogy to a full‐service set of stores in a shopping mall.

This paper aims to explore FinTech and its dynamic transitions in the banking industry. In particular, the study analyses the systemic innovation nature of FinTech-based innovations. The main contribution of this research study is the development of systemic innovation model which can be used as a dynamic tool to track the progress and pattern of technology development and diffusion. The research also discusses the latest financial innovation of PromptPay FinTech – the e-payment system in Thailand.

This research uses the case study approach to analyse the systemic innovation characteristics of FinTech-based innovations. This research offers a new systemic innovation model which is developed and can be used as a dynamic tool to track the progress and pattern of technology development and diffusion. The study uses FinTech-based innovations as case study samples to gain a better understanding concerning the systemic characteristics and the pattern of technology diffusion under the analytical framework of systemic innovation model. This research involves qualitative interviews with five major commercial banks in the financial services industry of Thailand.

The analyses of findings show the systemic characteristics of FinTech-based innovations in the banking industry, both at a global scale and Thailand case. The analyses have shown that systemic characteristics of the innovation process are the outcome of interactions between the complexity of the innovation and the capabilities of innovators in managing the innovation. The insightful implications on the systemic nature of innovation give the trend and direction of FinTech-based innovation development in the banking industry.

The main contribution which shows originality and value of this paper is the development of systemic innovation model. This research study develops a systemic innovation model to analyse the systemic characteristics which can be applied to all innovations in any industry. The model can also help track the progress and pattern of technology development and diffusion. Therefore, the model can be used to project the trend and diffusion of innovation competition in the banking industry.

In this paper we present a CDN‐based system, namely the COMODIN system, which is a media on‐demand platform for synchronous cooperative work which supports an explicitly‐formed cooperative group of distributed users with the following integrated functionalities: request of an archived multimedia session, sharing of its playback, and collaboration through questioning. The server‐side architecture of the COMODIN system is organized into two integrated planes: the Base plane, which consists of a streaming CDN providing media streaming, and the Collaborative plane, which provides the collaborative playback service. At the client‐side, the system centers on a Java‐based application which interfaces the cooperative group of users.

This paper seeks to investigate and provide empirical evidence of the interrelationships among network externalities, e‐business adoption and information asymmetry.

A conceptual model was proposed and tested using 307 completed interview cases selected from a database of 2,075 Chinese international trading companies published by the Beijing Municipal Bureau of Commerce for this study.

The results indicated that network externalities significantly influenced e‐business adoption and information asymmetry, and e‐business adoption influenced information asymmetry through information sharing and collection. A split sample analysis showed that cultural contexts significantly moderated the interrelationships among network externalities, e‐business adoption, and information asymmetry.

Data for this study were collected only from mainland China, therefore, non‐Chinese companies (foreign‐owned) operating in China may have been influenced by Chinese cultures and some of them have been localizing their operations in China. The influences of network externalities on business performance and decision making remain unclear. In addition, data were collected from self‐reported questionnaires, and thus may be subject to self‐reporting bias. Future studies should use more objective measurements to reduce the potential for self‐reporting bias.

This study contributes significantly to the literature by providing empirical evidence on interrelationships among network externalities, e‐business adoption, and information asymmetry. The findings in this study also provide valuable insights for managers to better understand the influence of network externalities on e‐business adoption.

This study contributes significantly to the literature by providing empirical evidence of the interrelationships among network externalities, e‐business adoption, and information asymmetry. The findings also provide managers with valuable insight into better understanding of the nature of these interrelationships.

In a complex semiconductor manufacturing system (SMS) environment, the implementation of dynamic production scheduling and dispatching strategies is critical for SMS distributed collaborative manufacturing events to make quick and correct decisions. The purpose of this paper is to assist manufacturers in achieving the real time dispatching and obtaining integrated optimization for shop floor production scheduling.

In this paper, an integrated model is designed under assemble to order environment and a framework of a real time dispatching (IRTD) system for production scheduling control is presented accordingly. Both of the scheduling and ordering performances are integrated into the days of inventory based dispatching algorithm, which can deal with the multiple indicators of dynamic scheduling and ordering in this system to generate the “optimal” dispatching policies. Subsequently, the platform of IRTD system is realized with four modules function embedded.

The proposed IRTD system is designed to compare the previous constant work in process method in the experiment, which shows the better performance achievement of the IRTD system for shop floor production dynamic scheduling and order control. The presented framework and algorithm can facilitate real time dispatching information integration to obtain performance metrics in terms of reliability, availability, and maintainability.

The presented system can be further developed to generic factory manufacturing with the presented logic and architecture proliferation.

The IRTD system can integrate the real time customer demand and work in process information, based on which manufacturers can make correct and timely decisions in solving dispatching strategies and ordering selection within an integrated information system.