ALBERT

Description: The rabid growth of today’s technological world has led us to connecting every electronic device worldwide together, which guides us towards the Internet of Things (IoT). Gathering the produced information based on a very tiny sensing devices under the umbrella of Wireless Sensor Networks (WSNs). The nature of these networks suffers from missing sharing among them in both hardware and software, which causes redundancy and more budget to be used. Thus, the appearance of Shared Sensor Networks (SSNs) provides a real modern revolution in it. Where it targets making a real change in its nature from domain specific networks to concurrent running domain networks. That happens by merging it with the technology of virtualization that enables the sharing feature over different levels of its hardware and software to provide the optimal utilization of the deployed infrastructure with a reduced cost. This article is concerned with surveying the idea of SSNs, the difference between it and the traditional WSNs, the requirements for its construction, challenges facing it, and the opportunities that are provided by it, then describing our proposed architectures. As a result of using virtualization technology as a basic block in building SSNs, using different types of virtualization will produce different types of SSNs that will give different usages to it. This article proposes a novel approach of taxonomy for SSNs that is based on the used virtualization techniques, and it describes the needs and usages of each one. It presents a wide array of previously proposed solutions comparing them to each other and a brief description of the issues addressed by each category of that taxonomy. Additionally, the shared sensor architecture and shared network architecture were depicted. Finally, some of its applications in some daily life fields are listed.

Description: Various technologies and standards for the Internet of Things (IoT) have defined the way devices should interact with each other to provide an intelligent IoT service to users in an efficient manner. Although the usability of system interface between the platform and users is one of the key factors for the success of IoT ecosystems, the manner in which IoT platforms should interact with users has not been well studied. Current IoT platforms provide a simple list-based interface to manage devices, which result in the degradation of their usability as the number of devices increases. In this paper, we propose an interactive web-based IoT management system where deep object detection techniques are adopted to facilitate user’s device selection and management. The proposed system automatically recognizes the device type from video streams and accordingly generates smart controllers. The users can choose a device by touching an object in the video stream and use a smart controller to control the selected device. Finally, we show the feasibility of the proposed system through the implementation of a prototype which demonstrates a set of user scenarios.

Description: This study provides a mathematical model and theoretical analysis of an interference cancellation system combining an orthogonal matched filter (OMF) and adaptive array antenna that is called the extended OMF (EOMF). In recent years, an increase in the number of applications of mobile ad hoc networks (MANETs) is expected. To realize a highly reliable MANET, it is essential to introduce a method for cancelling the interference from other nodes. This research focuses on a scheme based on Code Division Multiple Access (CDMA) that enables simultaneous multiple access and low latency communication. However, there are problems with deteriorating performance due to the near–far problem and the increase in the amount of interference as the number of users increases. Additionally, another problem is that the spreading sequence of each user is unknown in a MANET. The OMF is expected to be a solution to these problems. The OMF performs interference cancellation by generating and subtracting a replica of the interference signal that is contained in the received signal. However, the OMF may generate an incorrect replica in the near–far problem. The EOMF compensates for the OMF’s weakness by combining the OMF with an adaptive array antenna. In this research, optimal parameters are derived from mathematical modelling and theoretical analysis of the EOMF. Specifically, the optimal weight vector and the minimum mean squared error that allow the adaptive algorithm to converge are derived and obtained from the numerical results.

Description: This paper presents a framework to accurately and non-intrusively detect the number of people in an environment and track their positions. Different from most of the previous studies, our system setup uses only ambient thermal sensors with low-resolution, using no multimedia resources or wearable sensors. This preserves user privacy in the environment, and requires no active participation by the users, causing no discomfort. We first develop multiple methods to estimate the number of people in the environment. Our experiments demonstrate that algorithm selection is very important, but with careful selection, we can obtain up to 100% accuracy when detecting user presence. In addition, we prove that sensor placement plays a crucial role in the system performance, where placing the sensor on the room ceiling yields to the best results. After accurately finding the number of people in the environment, we perform position tracking on the collected ambient data, which are thermal images of the space where there are multiple people. We consider position tracking as static activity detection, where the user’s position does not change while performing activities, such as sitting, standing, etc. We perform efficient pre-processing on the data, including normalization and resizing, and then feed the data into well-known machine learning methods. We tested the efficiency of our framework (including the hardware and software setup) by detecting four static activities. Our results show that we can achieved up to 97.5% accuracy when detecting these static activities, with up to 100% class-wise precision and recall rates. Our framework can be very beneficial to several applications such as health-care, surveillance, and home automation, without causing any discomfort or privacy issues for the users.

Description: Nowadays, the penetration of sensors and actuators in different application fields is revolutionizing all aspects of our daily life. One of the major sectors that is taking advantage of such cutting-edge cheap smart devices is healthcare. In this context, Remote Patient Monitoring (RPM) at home represents a tempting opportunity for hospitals to reduce clinical costs and to improve the quality of life of both patients and their families. It allows patients to be monitored remotely by means networks of Internet of Things (IoT) medical devices equipped with sensors and actuators that collect healthcare data from patients and send them to a Cloud-based Hospital Information System (HIS) for processing. Up to now, many different proprietary software systems have been developed as stand-along expensive solutions, presenting interoperability, extensibility, and scalability issues. In recent years, the European Commission (EC) has promoted the wide adoption of FIWARE technology, launching 16 Industrial Accelerators focusing on different application fields. One of these, i.e., FICHe, is specialized in healthcare, providing the guidelines on how to develop eHealth systems. This paper focuses on how to compose new cutting-edge IoT and Cloud-based Cyber Physical Health Sytem (CPHS) services and applications interconnected with remote medical sensors and actuators using FIWARE technology in the context envisioned by FICHe. In particular, we discuss the design and development of an RPM system implemented through the collaboration between the Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) “Bonino Pulejo” (i.e., a clinical and research healthcare centre specialized in the treatment of neuro lesions), University of Messina, IBM Research, Telefónica, and the University of the Western Cape in South Africa. The description of our best practice provides a model and guidelines for the development of lightweight and low cost RPM services for rural and isolated areas, with the expectation of expanding healthcare to the developing world and in general allows us to outline how to deal with the real adoption of the FIWARE technology in an e-health project.

Description: The paper addresses the problem of localization based on hybrid received signal strength (RSS) and time of arrival (TOA) measurements, in the presence of synchronization errors among all the nodes in a wireless network, and assuming all parameters are unknown. In most existing schemes, in fact, knowledge of the model parameters is postulated to reduce the high dimensionality of the cost functions involved in the position estimation process. However, such parameters depend on the operational wireless context, and change over time due to the presence of dynamic obstacles and other modification of the environment. Therefore, they should be adaptively estimated “on the field”, with a procedure that must be as simple as possible in order to suit multiple real-time re-calibrations, even in low-cost applications, without requiring human intervention. Unfortunately, the joint maximum likelihood (ML) position estimator for this problem does not admit a closed-form solution, and numerical optimization is practically unfeasible due to the large number of nuisance parameters. To circumvent such issues, a novel two-step algorithm with reduced complexity is proposed: A first calibration phase exploits nodes in known positions to estimate the unknown RSS and TOA model parameters; then, in a second localization step, an hybrid TOA/RSS range estimator is combined with an iterative least-squares procedure to finally estimate the unknown target position. The results show that the proposed hybrid TOA/RSS localization approach outperformed state-of-the-art competitors and, remarkably, achieved almost the same accuracy of the joint ML benchmark but with a significantly lower computational cost.

Description: In energy detection for cognitive radio spectrum sensing, the noise variance is usually assumed given, by which a threshold is set to guarantee a desired constant false alarm rate (CFAR) or a constant detection rate (CDR). However, in practical situations, the exact information of noise variance is generally unavailable to a certain extent due to the fact that the total noise consists of time-varying thermal noise, receiver noise, and environmental noise, etc. Hence, setting the thresholds by using an estimated noise variance may result in different false alarm probabilities from the desired ones. In this paper, we analyze the basic statistical properties of the false alarm probability by using estimated noise variance, and propose a method to obtain more suitable CFAR thresholds for energy detection. Specifically, we first come up with explicit descriptions on the expectations of the resultant probability, and then analyze the upper bounds of their variance. Based on these theoretical preparations, a new method for precisely obtaining the CFAR thresholds is proposed in order to assure that the expected false alarm probability can be as close to the predetermined as possible. All analytical results derived in this paper are testified by corresponding numerical experiments.

Description: Historically, universities and institutions of higher learning have gone through three academic revolutions, namely, teaching, research, and innovation. Universities and Higher Educational Institutions (HEIs) in the last two decades have come to occupy an important part in the national innovation systems (NIS), which is a complex of ‘all important economic, social, political, organizational, institutional and other factors that influence the development, diffusion and use of innovations’. From a broader perspective, universities, together with public Research and Development (R&D) labs and science agencies, public policies (on industry, research, innovation and higher education, etc.) and business enterprises are now considered as important actors in the NIS of Asia-Pacific economies. The rise of Asia in the global knowledge-based economy from mid-1990s is closely associated with the rise of knowledge institutions of higher learning and scientific research output. Every Asia-Pacific country embraced and introduced policies relating to innovation in varying forms. Consultancy and collaborative links with industry being traditional forms of engagement, new policy and institutional measures in technology transfer and innovation to engage with society and business enterprises are gaining prominence. Policies for incubation, start-ups, and spin-offs, technology transfer offices (TTOs), and science and technology parks have gained tremendous prominence in leading Asia-Pacific universities. Different national innovation systems in the Asia-Pacific region have given rise to varying roles of universities. Whilst universities in Southeast Asian countries and India continue to play a traditional role of teaching and generating human capital, there are countries such as Singapore, China, Taiwan, and Japan, wherein universities are being transformed as entrepreneurial universities. Science and innovation policies in these countries have orchestrated the goal direction of universities as frontiers of innovation. Universities in Australia and New Zealand have so far been quite successful in marketing higher education to neighboring Asian countries. They have in recent years begun to embark on innovation and commercialization of research. The paper focuses on South East Asia and draws some comparison with more dynamic university ecosystems in East Asia. In doing so, the paper brings into focus the emerging innovation landscapes across the region.

Description: Nowadays, new energy vehicles play an important role in the transformation and upgrade of China’s energy security, energy conservation and other industries. At present, there are 26 pilot cities for the demonstration of new energy vehicles in China; however, the operation effect and experience of the pilot cities have been summarized less. This paper takes Shenzhen’s new energy vehicle industry policy as the object of research, in order to explore the impact of demand innovation on the development of new energy vehicles. This paper summarizes the three stages of Shenzhen’s new energy vehicle industry promotion, and further analyzes the policy and market environments of each stage by using the demand-side innovation policy theory. By reflecting on the concept of policy design, this paper proposes that decision makers need to cultivate open innovative thinking, and transform their production-oriented policy design into a demand-oriented policy design. This conclusion is helpful for pilot cities in order to adjust their policies over time according to the different stages of industrial development, and further improve the innovation and competitiveness of China’s new energy vehicle industry.

Description: This conceptual paper examines the still under-researched phenomena associated with internationalization within the context of entrepreneurial ecosystems. Drawing on multiple literature streams, I develop TCKF-Connect, a cross-disciplinary conceptual framework to investigate how entrepreneurial ecosystems become globally connected, and how, in turn, an ecosystem’s global connectedness can drive and sustain the internationalization processes of innovative start-ups. I propose a distinction between entrepreneurial ecosystems’ connectivity and ecosystems’ connectedness, where the former is purported as a necessary but not sufficient condition to achieve the latter. The framework developed revolves around the role played by a specific “vehicle” of connectivity across entrepreneurial ecosystems, i.e., temporary clusters, as conceptualized by Maskell, Bathelt and Malmberg and focuses on the role of knowledge flows within temporary clusters and across the entrepreneurial ecosystems where the temporary clusters are nested. The cross-disciplinary conceptual framework developed contributes to both research and policy debates by underpinning the investigation of research questions to further our understanding of the interplay between internationalization of entrepreneurial ecosystems and internationalization of the start-ups nested within them. The article proposes a research agenda emanating from the application of the cross-disciplinary conceptual framework developed and suggests a methodology for the empirical investigation.

Description: The study aims to identify motivational factors that lead to collective intelligence and understand how these factors relate to each other and to innovation in enterprises. The study used the convenience sampling of corporate employees who use collective intelligence from corporate panel members (n = 1500). Collective intelligence was found to affect work process, operations, and service innovation. When corporate employees work in an environment where collective intelligence (CI) is highly developed, work procedures or efficiency may differ depending on the onset of CI. This raises the importance of CI within an organization and implies the importance of finding means to vitalize CI. This study provides significant implications for corporations utilizing collective intelligence services, such as online communities. Firstly, such corporations vitalize their services by raising the quality of information and knowledge shared in their workplaces; and secondly, contribution motivations that consider the characteristics of knowledge and information contributors require further development.

Description: The financial valuation of a drug that is still under development is required for various purposes. The risk-adjusted net present value (r-NPV) method, which recently emerged in the biotech industry, uses the development attrition rate as a discount factor to reflect risk during each development phase. The r-NPV method was developed to overcome the disadvantages of the prevailing discounted cash flow and real options methods and considers drug type, as well as the stage of development in its approach. Using this method, the current study examines technology values in the biopharmaceutical industry and matches the clinical development periods and success rates of these new drugs by analyzing datasets from ClinicalTrials.gov and MedTrack DB. It thus provides support for an empirical valuation model for experts in the field. Notably, there is limited research on the attrition rate and development period of new substance drugs and the research results are not consistently presented. In addition to new substance drugs, further research is necessary to deepen understanding of the attrition rate and development period of biologically-based drugs because of their inherent physical and developmental differences. Similarly, research on performance specifics within drug class models would enable refinement of the model.

Description: This research aimed to present a solution to the problem of production scheduling and assignment in broiler farms, which thus enabled the farms to achieve maximum profit. In the operation of farms, there are many factors that affect profits, such as the number of broilers being consistent with the demand of production plants, including profits from the sales and transportation costs. Therefore, we formulated a mathematical model and tested it while using three problem groups through the Lingo v.11 program. The results indicated that this mathematical model could find a suitable solution. However, finding the best solution had time constraints, which resulted in various other problems that prevented a search for an optimal solution due to time consumption exceeding 72 h. We developed an algorithm using the Adaptive Large Neighborhood Search (ALNS) method in order to find another possible solution using a shorter time period, which consisted of ALNS1, ALNS2, and ALNS3. These algorithms are based on a combination of the method of destruction solutions and methods accepting different solutions. We aimed to effectively solve the problems and ensure that they are appropriate for the case study, a broiler farm in Buriram. When comparing the algorithm efficiency with the Lingo v.11 program, it was found that the ALNS1 algorithm was the most suitable for finding the optimal solution in the shortest time, which resulted in a 5.74% increase in operating profits.

Description: Due to low activity in Internet of Things (IoT) applications, systems tend to leverage low power modes in order to reduce their power consumption. Normally-off computing thus arose, consisting in having turned off most part of a system’s power supply, while dynamically turning on components as the application needs it. As wake up sources may be diverse, simple controllers are integrated to handle smart wake up schemes. Therefore, to prevent overconsumption while transitioning to running mode, fast wake up sequences are required. An asynchronous 16-bit Reduced Instruction Set Computer (RISC) Wake-up Controller (WuC) is proposed demonstrating 50.5 ns@9.2 Million Instructions Per Second (MIPS)@0.6 V wake-up latency, drastically reducing the overall wake-up energy of IoT systems. A clockless implementation of the controller saves the booting time and the power consumption of a clock generator, while providing high robustness to environmental variations such as supply voltage level. The WuC is also able to run simple tasks with a reduced Instruction Set Architecture (ISA) and achieves as low as 11.2 pJ/inst @0.5 V in Fully Depleted Silicon On Insulator (FDSOI) 28 nm.

Description: Logging and tracking raw materials, workpieces and engineered products for seamless and quick pulls is a complex task in the construction and shipbuilding industries due to lack of structured storage solutions. Additional uncertainty is introduced if workpieces are stacked and moved by multiple stakeholders without maintaining an active and up-to-date log of such movements. While there are frameworks proposed to improve workpiece pull times using a variety of tracking modes based on deterministic approaches, there is little discussion of cases wherein direct observations are sparse due to occlusions from stacking and interferences. Our work addresses this problem by: logging visible part locations and timestamps, through a network of custom designed observation devices; and building a graph-based model to identify events that highlight part interactions and estimate stack formation to search for parts that are not directly observable. By augmenting the site workers and equipment with our wearable devices, we avoid adding additional cognitive effort for the workers. Native building blocks of the graph-based model were evaluated through simulations. Experiments were also conducted in an active shipyard to validate our proposed system.

Description: The incorporation of sustainable aspects in the supply chain management (SCM) has become an important topic for researchers and professionals; however, it is a field that yet lacks a systemic understanding. The objective of this article is to conduct an analysis on the international literature about the SCM sustainability topic, by employing a systematic review protocol, covering the period from 2011 to 2016. The content analysis technique was performed, following the procedures of categorical thematic analysis proposed by Bardin (1977), which considers the creation of categories a posteriori, based in the direction senses related to the content analyzed. Besides to present the main characteristics of the articles related to distribution of publications per year, most studied sectors, main methods and approaches used main countries and journals of publications, we categorize the results at the systemic approach level of the sustainable development dimensions. We found that some dimensions are prominent when compared with the others: For example: the environmental one, on the other hand, the social one is approached few times in the papers considered in our analysis. These results also indicate that this type of discussion needs to be extended to other sectors that have not yet been explored. The contribution of this paper lies on the synthetization of the state-of-the-art related to sustainable SCM in the period considered, highlighting the environmental, social and economic dimensions, in order to identify a research agenda. By identifying possible research gaps, the results of this research contribute to guide future investigations on sustainable SCM, aiding researchers and practitioners in this field.

Description: Blockchains are attracting the attention of stakeholders in many industrial domains, including the logistics and supply chain industries. Blockchain technology can effectively contribute in recording every single asset throughout its flow on the supply chain, contribute in tracking orders, receipts, and payments, while track digital assets such as warranties and licenses in a unified and transparent way. The paper provides, through its methodology, a detailed analysis of the blockchain fit in the supply chain industry. It defines the specific elements of blockchain that affect supply chain such as scalability, performance, consensus mechanism, privacy considerations, location proof and cost, and details on the impact that blockchains will have in disrupting the supply chain industry. Discussing the tradeoff between consensus cost, throughput and validation time it proceeds with a suggested high-level architectural approach, and concludes as a result with a discussion on changes needed and challenges faced for an in-vivo deployment of blockchains in the supply chain industry. While the technological features of modern blockchains can effectively facilitate supply chain uses cases, the various challenges that still remain, bring in front of us a wide set of needed changes and further research efforts for achieving a global, production level blockchain for the supply chain industry.

Description: Dairy farming is a subsidiary profession of agriculture in India where dairy cooperatives are an important part of rural development. The current study explores the critical factors in the dairy supply chain, and provides an initial decision framework for its implications. The necessary data were collected from dairy producer members including dairy farmers, executives, and key informants of processing units, to summarize the strengths, weaknesses, opportunities, threats (SWOT) of the milk processing system in India. This includes identifying the objectives of the dairy industry, along with the internal and external critical factors (CFs). SWOT exploration does not offer any investigative basis for evaluating the priorities of CFs, therefore the analytic hierarchy process is applied to define the priorities of identified CFs. The CFs have also been ordered according to relative importance. The findings of this study depict that the SWOT based methodology offers vital sensitivity in assessing the supply chain strategies for the dairy industry.

Description: As Internet of Things (IoT) involvement increases in our daily lives, several security and privacy concerns like linkability, unauthorized conversations, and side-channel attacks are raised. If they are left untouched, such issues may threaten the existence of IoT. They derive from two main reasons. One is that IoT objects are equipped with limited capabilities in terms of computation power, memory, and bandwidth which hamper the direct implementation of traditional Internet security techniques. The other reason is the absence of widely-accepted IoT security and privacy guidelines and their appropriate implementation techniques. Such guidelines and techniques would greatly assist IoT stakeholders like developers and manufacturers, paving the road for building secure IoT systems from the start and, thus, reinforcing IoT security and privacy by design. In order to contribute to such objective, we first briefly discuss the primary IoT security goals and recognize IoT stakeholders. Second, we propose a comprehensive list of IoT security and privacy guidelines for the edge nodes and communication levels of IoT reference architecture. Furthermore, we point out the IoT stakeholders such as customers and manufacturers who will benefit most from these guidelines. Moreover, we identify a set of implementation techniques by which such guidelines can be accomplished, and possible attacks against previously-mentioned levels can be alleviated. Third, we discuss the challenges of IoT security and privacy guidelines, and we briefly discuss digital rights management in IoT. Finally, through this survey, we suggest several open issues that require further investigation in the future. To the best of the authors’ knowledge, this work is the first survey that covers the above-mentioned objectives.

Description: Thanks to IEEE 802.15.4 defining the operation of low-rate wireless personal area networks (LR-WPANs), the door is open for localizing sensor nodes using tiny, low power digital radios such as Zigbee. In this paper, we propose a three-dimensional (3D) localization scheme based on well-known loop invariant for division algorithm. Parametric points are proposed by using the reference anchor points bounded in an outer region named as Parametric Loop Division (PLD) algorithm. Similar to other range-based localization methods, PLD is often influenced by measurement noise which greatly degrades the performance of PLD algorithm. We propose to adopt extended Kalman filtering (EKF) to refine node coordinates to mitigate the measurement noise. We provide an analytical framework for the proposed scheme and find the lower bound for its localization accuracy. Simulation results show that compared with the existing PLD algorithm, our technique always achieves better positioning accuracy regardless of network topology, communication radius, noise statistics, and the node degree of the network. The proposed scheme PLD-EKF provides an average localization accuracy of 0.42 m with a standard deviation of 0.26 m.

Description: Advances in the Internet of Things (IoT) are helping to make water management smarter and optimizing consumption in the smart agriculture industry. This article proposes a new topology of sensor nodes based on the use of inexpensive and highly efficient components, such as water level, soil moisture, temperature, humidity, and rain sensors. Additionally, to guarantee good performance of the system, the used transmission module is based on LoRa LPWAN technology. The design of the main circuit board of the system is optimized by combining two layers and implementing software optimization. The overall sensor network is developed and tested in the research lab, and real farms can be controlled by users manually or automatically using the mobile application. Experimental results are produced by testing sensor and communication link effectiveness, and are subsequently validated in the field through a one-week measurement campaign.

Description: In the Internet of Things (IoT), a huge number of sensors, actuators and other equipment for data acquisition and processing will be interconnected by means of an omnipresent communication network able to efficiently support heterogeneous transmission technologies and applications. On the one hand, advanced optical communication systems, which already play a significant role in modern networks, are currently evolving to meet very high requirements of modern applications. On the other hand, there are already many ways to utilize optical components and effects for building precise, efficient, and reliable sensors. Thus, optical technologies have the potential to greatly help in realizing future smart infrastructures and systems. This paper gives an overview of currently available and emerging optical technologies for sensing and communication applications and reviews their possible application in the context of the IoT for realizing smart systems and infrastructures.

Description: Industrial Control Systems (ICSs) are responsible for the automation of different processes and the overall control of systems that include highly sensitive potential targets such as nuclear facilities, energy-distribution, water-supply, and mass-transit systems. Given the increased complexity and rapid evolvement of their threat landscape, and the fact that these systems form part of the Critical National infrastructure (CNI), makes them an emerging domain of conflict, terrorist attacks, and a playground for cyberexploitation. Existing layered-defence approaches are increasingly criticised for their inability to adequately protect against resourceful and persistent adversaries. It is therefore essential that emerging techniques, such as orthogonality, be combined with existing security strategies to leverage defence advantages against adaptive and often asymmetrical attack vectors. The concept of orthogonality is relatively new and unexplored in an ICS environment and consists of having assurance control as well as functional control at each layer. Our work seeks to partially articulate a framework where multiple functional and assurance controls are introduced at each layer of ICS architectural design to further enhance security while maintaining critical real-time transfer of command and control traffic.

Description: Emerging Mobile Cloud Computing (MCC) technologies offer a new world of promise by leveraging the quality of mobile services. With MCC, resource-constrained mobile devices could capitalize on the computation/storage resources of cloud servers via communication networks. While MCC adoption is growing significantly, several challenges need to be addressed to make MCC-based solutions scale and meet the ever-growing demand for more resource intensive applications. Security is a critical problem hindering the adoption of MCC. One of the most important aspects of MCC security is to establish authenticated communication sessions between mobile devices and cloud servers. The huge amount of data stored on mobile devices poses information security risks and privacy concerns for individuals, enterprises, and governments. The ability to establish authenticated communication sessions between mobile devices and cloud servers can resolve many security concerns. Limited computing and energy resources on mobile devices makes authentication and encryption a challenging task. In this paper, an overview of MCC authentication protocols is presented. Then, a Dual-Factor Authentication Protocol for MCC devices (D-FAP) is proposed. D-FAP aims at increasing authentication security by using multi-factors while offloading computation to the cloud to reduce battery consumption. The security of the protocol is formally verified and informal analysis is performed for various attacks. The results prove that the D-FAP is successful in mitigating various outsider and insider attacks.

Description: By nature, some jobs are always in closed environments and employees may stay for long periods. This is the case for many professional activities such as military watch tours of borders, civilian buildings and facilities that need efficient control processes. The role assigned to personnel in such environments is usually sensitive and of high importance, especially in terms of security and protection. With this in mind, we proposed in our research a novel approach using multi-sensor technology to monitor many safety and security parameters including the health status of indoor workers, such as those in watchtowers and at guard posts. In addition, the data gathered for those employees (heart rate, temperature, eye movement, human motion, etc.) combined with the room’s sensor data (temperature, oxygen ratio, toxic gases, air quality, etc.) were saved by appropriate cloud services, which ensured easy access to the data without ignoring the privacy protection aspect of such critical material. This information can be used later by specialists to monitor the evolution of the worker’s health status as well as its cost-effectiveness, which gives the possibility to improve productivity in the workplace and general employee health.

Description: The Internet of things requires long-life wireless sensor nodes powered by the harvested energy from environments. This paper proposes a nonlinear electromagnetic energy harvesting system which may be used to construct fully self-powered wireless sensor nodes. Based on a nonlinear electromagnetic energy harvester (EMEH) with high output voltage, the model of a nonlinear interface circuit is derived and a power management circuit (PMC) is designed. The proposed PMC uses a buck–boost direct current-direct current (DC–DC) converter to match the load resistance of the nonlinear interface circuit. It includes two open-loop branches, which is beneficial to the optimization of the impedance matching. The circuit is able to work even if the stored energy is completely drained. The energy harvesting system successfully powered a wireless sensor node. Experimental results show that, under base excitations of 0.3 g and 0.4 g (where 1 g = 9.8 m·s−2) at 8 Hz, the charging efficiencies of the proposed circuit are 172% and 28.5% higher than that of the classic standard energy-harvesting (SEH) circuit. The experimental efficiency of the PMC is 41.7% under an excitation of 0.3 g at 8 Hz.

Description: Fifth-generation (5G) mobile systems are a necessary step toward successfully achieving further increases in data rates. As the use of higher-order quadrature amplitude modulation (QAM) is expected to increase data rates within a limited bandwidth, we propose a method for orthogonal frequency division multiplexing (OFDM)-based 1024- and 4096-QAM transmission with soft-decision Viterbi decoding for use in 5G mobile systems. Through evaluation of the transmission performance of the proposed method over multipath fading channels using link-level simulations, we determine the bit error rate (BER) performance of OFDM-based 1024- and 4096-QAM as a function of coding rate under two multipath fading channel models: extended pedestrian A (EPA) and extended vehicular A (EVA). We also demonstrate the influence of phase error on OFDM-based 1024- and 4096-QAM and clarify the relationship between phase error and the signal-to-noise ratio (SNR) penalty required to achieve a BER of 1 × 10−2. This work provides an effective solution for introducing higher-order modulation schemes in 5G and beyond.

Description: Ambient gas detection and measurement had become essential in diverse fields and applications, from preventing accidents, avoiding equipment malfunction, to air pollution warnings and granting the correct gas mixture to patients in hospitals. Gas leakage can reach large proportions, affecting entire neighborhoods or even cities, causing enormous environmental impacts. This paper elaborates on a deep review of the state of the art on gas-sensing technologies, analyzing the opportunities and main characteristics of the transducers, as well as towards their integration through the Internet of Things (IoT) paradigm. This should ease the information collecting and sharing processes, granting better experiences to users, and avoiding major losses and expenses. The most promising wireless-based solutions for ambient gas monitoring are analyzed and discussed, open research topics are identified, and lessons learned are shared to conclude the study.

Description: An accurate 3-D wireless local positioning system (LPS) is a highly demanded tool for increasing safety in, e.g., emergency response and security operations. An LPS is an attractive approach that can meet stringent requirements and can achieve acceptable accuracies for a long time during extended operations in global navigation satellite system (GNSS)-denied environments. In this work, three closed-form (CF) least squares (LS) algorithms were considered, where two of them were adapted to exploit the knowledge about nuisance parameters for accurate 3-D positioning based on time difference of arrival (TDoA) measurements. The algorithms utilize the single set (SS) of the TDoA measurements, an extended SS (ExSS) of the TDoA measurements, or the full set (FS) of the TDoA measurements, and were denoted, respectively, as the CFSSLS, CFExSSLS, and CFFSLS solutions. The performance of the algorithms was investigated with simulations and real-world measurements, where the wireless system transmitters were placed in a quasi-coplanar arrangement. At moderate to high signal-to-noise ratio (SNR) levels, the CFSSLS solution has the best performance, followed by the CFExSSLS solution and then by the CFFSLS solution. At low SNR levels, the CFFSLS algorithm outperformed the other two algorithms. Both the CFSSLS and CFFSLS solutions estimate nuisance parameters that are utilized in refining the vertical position estimate of the receiver. The CFFSLS solution delivers more accurate refined vertical position estimates since it utilizes more nuisance parameters, i.e., more information. The experimental results confirmed the simulation study in which the CFFSLS algorithm outperformed the other two algorithms, where the experimental environment was dominated by total non-line-of-sight (NLoS) conditions and low SNR levels at the receiver to be located. Therefore, it is recommended to use the FS TDoA measurements for 3-D positioning in bad signal conditions, such as high noise levels and NLoS propagation.

Description: With the increase of mobile terminals, routing protocols in wireless communications must provide better quality of service to meet bandwidth and reliability requirements. In networks without infrastructure, such as ad hoc and sensor networks, where a device performs as both a terminal and a router to forward data of other nodes, maintaining the network topology consumes considerable resources in terms of energy and bandwidth. These parameters need to be considered when designing routing protocols for wireless networks. To reduce the cost of the protocol overhead, some algorithms act on the forwarders, while others act on the transmission of messages. Finally, the hybrid ones are a combination of both. In this paper, we propose a new algorithm with two zoning strategies to enhance the performance of mobile network. The first strategy helps to select dispersive forwarders in order to reduce the collision in radio channel. The second strategy aims to reduce the transmission of redundant messages. Both strategies are based on the location information of nodes. We implemented our algorithm in the optimized link state routing protocol, the most used protocol in mobile ad hoc networks. We showed by simulations that our solution reduces drastically the cost of the overhead with no hindrance to the network topology.

Description: The use of completely automated systems for collecting sensor data with the aim of monitoring and controlling the quality of small-scale food processes is not widespread. Small and micro-enterprises usually do not carry out their own precompetitive research or prototype development as regards to automation technologies. This study proposes a web-based, low-cost monitoring and supervisory control and data acquisition (SCADA) system whose kernel is available for free, as a possible solution that could be adopted by these food producers. It is mainly based on open SW/HW so as its configuration is adaptable to the application and type of plant. It presents a modular architecture and its main functionalities encompass the acquisition, management, aggregation and visualization of process data, providing an operating database. It also provides food tracking and process quality control: The time series are browsable due to QR-Code generation and different early warning detection strategies are implemented. A tool for solving migration problems based on Fick’s equation is offered as a packaging decision support system.

Description: The global connected cars market is growing rapidly. Novel services will be offered to vehicles, many of them requiring low-latency and high-reliability networking solutions. The Cloud Radio Access Network (C-RAN) paradigm, thanks to the centralization and virtualization of baseband functions, offers numerous advantages in terms of costs and mobile radio performance. C-RAN can be deployed in conjunction with a Multi-access Edge Computing (MEC) infrastructure, bringing services close to vehicles supporting time-critical applications. However, a massive deployment of computational resources at the edge may be costly, especially when reliability requirements demand deployment of redundant resources. In this context, cost optimization based on integer linear programming may result in being too complex when the number of involved nodes is more than a few tens. This paper proposes a scalable approach for C-RAN and MEC computational resource deployment with protection against single-edge node failure. A two-step hybrid model is proposed to alleviate the computational complexity of the integer programming model when edge computing resources are located in physical nodes. Results show the effectiveness of the proposed hybrid strategy in finding optimal or near-optimal solutions with different network sizes and with affordable computational effort.

Description: Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.

Description: The Robotic Vessels as-a-Service (RoboVaaS) project intends to exploit the most advanced communication and marine vehicle technologies to revolutionize shipping and near-shore operations, offering on-demand and cost-effective robotic-aided services. In particular, the RoboVaaS vision includes a ship hull inspection service, a quay walls inspection service, an antigrounding service, and an environmental and bathymetry data collection service. In this paper, we present a study of the underwater environmental data collection service, performed by a low-cost autonomous vehicle equipped with both a commercial modem and a very low-cost acoustic modem prototype, the smartPORT Acoustic Underwater Modem (AHOI). The vehicle mules the data from a network of low cost submerged acoustic sensor nodes to a surface sink. To this end, an underwater acoustic network composed by both static and moving nodes has been implemented and simulated with the DESERT Underwater Framework, where the performance of the AHOI modem has been mapped in the form of lookup tables. The performance of the AHOI modem has been measured near the Port of Hamburg, where the RoboVaaS concept will be demonstrated with a real field evaluation. The transmission with the commercial modem, instead, has been simulated with the Bellhop ray tracer thanks to the World Ocean Simulation System (WOSS), by considering both the bathymetry and the sound speed profile of the Port of Hamburg. The set up of the polling-based MAC protocol parameters, such as the maximum backoff time of the sensor nodes, appears to be crucial for the network performance, in particular for the low-cost low-rate modems. In this work, to tune the maximum backoff time during the data collection mission, an adaptive mechanism has been implemented. Specifically, the maximum backoff time is updated based on the network density. This adaptive mechanism results in an 8% improvement of the network throughput.

Description: The use of wireless sensor networks, which are the key ingredient in the growing Internet of Things (IoT), has surged over the past few years with a widening range of applications in the industry, healthcare, agriculture, with a special attention to monitoring and tracking, often tied with security issues. In some applications, sensors can be deployed in remote, large unpopulated areas, whereas in others, they serve to monitor confined busy spaces. In either case, clustering the sensor network’s nodes into several clusters is of fundamental benefit for obvious scalability reasons, and also for helping to devise maintenance or usage schedules that might greatly improve the network’s lifetime. In the present paper, we survey and compare popular and advanced clustering schemes and provide a detailed analysis of their performance as a function of scale, type of collected data or their heterogeneity, and noise level. The testing is performed on real sensor data provided by the UCI Machine Learning Repository, using various external validation metrics.

Description: In underground (UG) multiple-input and multiple-output (MIMO), transmit beamforming is used to focus energy in the desired direction. There are three different paths in the underground soil medium through which the waves propagate to reach the receiver. When the UG receiver receives a desired data stream only from the desired path, then the UG MIMO channel becomes a three-path (lateral, direct, and reflected) interference channel. Accordingly, the capacity region of the UG MIMO three-path interference channel, and the degrees of freedom (multiplexing gain of this MIMO channel) requires careful modeling. Therefore, expressions are required for the degrees of freedom of the UG MIMO interference channel. The underground receiver needs to perfectly cancel the interference from the three different components of the EM waves propagating in the soil medium. This concept is based upon reducing the interference of the undesired components to a minimum level at the UG receiver using the receive beamforming. In this paper, underground environment-aware MIMO using transmit and receive beamforming has been developed. The optimal transmit and receive beamforming, combining vectors under minimal intercomponent interference constraints, are derived. It is shown that UG MIMO performs best when all three components of the wireless UG channel are leveraged for beamforming. The environment-aware UG MIMO technique leads to three-fold performance improvements and paves the way for design and development of next-generation sensor-guided irrigation systems in the field of digital agriculture. Based on the analysis of underground radio-wave propagation in subsurface radio channels, a phased-array antenna design is presented that uses water content information and beam-steering mechanisms to improve efficiency and communication range of wireless underground communications. It is shown that the subsurface beamforming using phased-array antennas improves wireless underground communications by using the array element optimization and soil–air interface refraction adjustment schemes. This design is useful for subsurface communication system where sophisticated sensors and software systems are used as data collection tools that measure, record, and manage spatial and temporal data in the field of digital agriculture.

Description: A new positioning algorithm for distance measurement systems is outlined herein. This algorithm utilizes a non-linear error function which allows us to improve the positioning accuracy in highly difficult indoor environments. The non-linear error function also allows us to adjust the performance of the algorithm to the particular environmental conditions. The well-known positioning algorithms have limitations, mentioned by their authors, which make them unsuitable for positioning in an indoor environment. In this article, there is a brief discussion about the most popular positioning algorithms with consideration of the indoor environment. The new positioning algorithm is described in detail and a comparative performance analysis of the well-known algorithms and the proposed one is conducted. Those research results are achieved with the utilization of real distance measurement data, collected inside a few different buildings, and they show that the proposed algorithm outperforms the Chan and Foy algorithms in indoor environments. In this article the Automatic Person Localization System (SALOn) is also presented, which was utilized to collect measurement data.

Description: In the current era of Industrial 4.0, open innovation, and the sharing economy, innovation ecosystems are formed through government-industry-university (triple helix) interaction. The concept of responsible innovation has emerged to explore how innovation can be conducted in a transparent, trustworthy, and sustainable way so as to respond to the public interest. While current literature provides a conceptual framework, details of how responsible innovation can be formed, developed, and sustained in the sharing economy, in particular in developing countries, have been under-explored. This paper aims to explore factors of responsible innovation, linking dimensions with business practice, and identify the dynamic stages of the industry life cycle. Through an in-depth case study of China’s shared bicycle industry and the firm Hellobike, this paper has prioritized factors which lead to responsibility, such as user safety and friendliness in product design, real-time operations combined with big data, collaboration between industry and local government for industry standardization, and user credit systems. It has enriched key dimensions based on literature and case studies and proposed dynamic interaction models for industry, government, users, and universities at different stages of responsible innovation in the shared bicycle sector. From this empirical study, future research areas have been identified.

Description: As the number of Internet of Things (IoT) devices increases, services expand and illegal hacking and infringement methods become more sophisticated, an effective solution for blockchain technology is required as a fundamental solution to security threats. In this paper, we develop the security module of an IoT device based on blockchain technology that blocks hacking and information infringement and forms a multi-security blockchain system between the IoT device and the user device and we develop a user application. We contribute to addressing the security threats faced by IoT application services by developing a new method. In particular, we present some schemes for the development of a multi-security certification system based on blockchain for IoT security.

Description: The platform business model is widely used because it is capable of various open innovation deliverables. However, it has a high probability of failure, caused by a variety of value streams that follow the two-sided market theory (each side has a distinct group of users). Therefore, extensive research on value streams and the attributes of platform business is essential to reduce platform business failure and ensure sustainable growth. By analyzing 21 case studies and conducting 30 in-depth interviews, this study proposes three types of Internet platform business strategies which can serve as a frame of reference to examine the impact of different value streams and open innovation on platform businesses. This study highlights a typology that sheds light on the heterogeneous meaning that corporates associated with creating new platform businesses adhere to and seeks to improve understanding of fundamental differences in platform business creation processes.

Description: This paper compares creativity experiences and perceptions among employees of small and medium-sized enterprises (SME) and students in higher education institutions (HEI) in Brunei Darussalam. The study was conducted through interactions and surveys to assess (i) understanding and practice of creative tools and techniques; (ii) creativity performance in teams and individuals and (iii) perception of creativity among 39 employees in SME and 68 students from HEI. Statistical analysis was carried out using Pearson’s chi-square test for goodness of fit and Cramer’s V test to estimate strength tests for correlation. The findings indicate a majority in both groups have not received prior instruction in creativity and that employees of SMEs have less interest in receiving creative instructions. There is consensus among both groups that group work will result in greater creative performance. Ambiguity of customer needs or requirement was a factor most often cited to impede creative performance of teams in SME. Results from this study were used to make recommendations to improve practice and learning creativity in SME and HEI.

Description: The purpose of this research is to study the factors related to the performance of the entrepreneurs who passed through the stages of business development at the university business incubators in Thailand. These factors consist of various characteristics, namely, leadership orientation, entrepreneurial orientation, network capacity, and innovative capacity. The sample group consisted of 220 businesses that had passed through a university business incubator in Thailand. The SPSS Statistics program calculated the basic statistics, as well as the relationship test for each factor studied, and examined the statistics using a structural equation model (SEM). The results revealed that the characteristics of leadership orientation, entrepreneurial orientation, network capacity, innovative capacity, and entrepreneurial performance had relationships in the same direction. Furthermore, an analysis of the relationships between the factors found that entrepreneurial orientation had positive relationships with network capacity and innovative capacity, leadership orientation had positive relationships with innovative capacity and entrepreneurial performance, and innovative capacity had a positive relationship with entrepreneurial performance. These relationships summarize a developmental model for the innovative capacity and performance of businesses that have passed through the university business incubators in Thailand.

Description: Nowadays, organizations are trying to have, not only a competitive advantage in the market, but also in sustainable development. The purpose of this paper is to investigate the process of measuring organizations’ sustainability using process-oriented indicators. The research seeks to address the following research question: How are process-oriented indicators linked to an organization’s strategy in the context of sustainable development? This research is based on reviewing the literature on organizational performance analysis in the context of sustainable development. The literature review highlights the main elements of organizational performance analysis and linkages to the overall business strategy. There are many ways of how to conduct an in depth assessment of an organization’s performance regarding sustainability. The research shows the elements that are integrated in the process and the organization’s performance analysis. These elements are—objectives, metrics, data measures, indicators and key performance indicators (KPIs). The research shows that growing organizations with a strategic focus on sustainability integrate these elements in the process analysis.

Description: Artificial intelligence (AI) has been altering industries as evidenced by Airbnb, Uber and other companies that have embraced its use to implement innovative new business models. Yet we may not fully understand how this emerging and rapidly advancing technology influences business model innovation. While many companies are being made vulnerable to new competitors equipped with AI technology, this study attempts to focus on the proactive side of the use of AI technology to drive business model innovation. Describing AI technology as the catalyst of business model innovation, this study sheds light on contingent factors shaping business model innovation initiated by the emerging technology. This study first provides a brief overview of AI, current issues being tackled in developing AI and explains how it transforms business models. Our case study of two companies that innovated their business models using AI shows its potential impact. We also discuss how executives can create an innovative AI-based culture, which rephrases the process of AI-based business model innovation. Companies that successfully capitalize on AI can create disruptive innovation through their new business models and processes, enabling them to potentially transform the global competitive landscape.

Description: Financial innovation by means of Fintech firms is one of the more disruptive business model innovations from the latest years. Specifically, in the financial advisor sector, worldwide assets under management of artificial intelligence (AI)-based investment firms, or robo-advisors, currently amount to US$975.5 B. Since 2008, robo-advisors have evolved from passive advising to active data-driven investment management, requiring AI models capable of predicting financial asset prices on time to switch positions. In this research, an artificial neural network modelling framework is specifically designed to be used as an active data-driven robo-advisor due to its ability to forecast with today’s copper prices five days ahead of changes in prices using input data that can be fed automatically in the model. The model, tested using data of the two periods with a higher volatility of the returns of the recent history of copper prices (May 2006 to September 2008 and September 2008 to September 2010) showed that the method is capable of predicting in-sample and out-of-sample prices and consequently changes in prices with high levels of accuracy. Additionally, with a 24-day window of out-of-sample data, a trading simulation exercise was performed, consisting of staying long if the model predicts a rise in price or switching to a short position if the model predicts a decrease in price, and comparing the results with the passive strategies, buy and hold or sell and hold. The results obtained seem promising in terms of both statistical and trading metrics. Our contribution is twofold: 1) we propose a set of input variables based on financial theory that can be collected and fed automatically by the algorithm. 2) We generate predictions five days in advance that can be used to reposition the portfolio in active investment strategies.

Description: Open innovation contributes to serving the customers of organizations with higher quality, as the customers become an active part of the innovation process. A successful solution for implementing open innovation can be achieved if organizations first create a total quality management (TQM) culture and then build on this foundation an ISO 9004:2018. The success of a quality management system depends first and foremost on the attitudes of the stakeholders, and the importance of technological and other conditions is only secondary. The goal in developing a successful philosophy of TQM is to build and sustain the leaderships’ and employees’ commitment, while the key to the success of ISO 9004:2018 is to establish and maintain the employees’ commitment and customer loyalty. The case study presented in this article demonstrates the need to increase the affective and normative commitment of leaders and employees in TQM, and after its implementation, there is a need to increase the employees’ continued commitment and customer loyalty in ISO 9004:2018 in order to succeed in quality management systems and open innovation.

Description: With technology advancement, industrial revolution 4.0, businesses nowadays are in competition in terms of product, service and business model innovation. Meanwhile, the emergent socio-ecological crisis is making it increasingly important to identify the impact of business on environment and the society. To date, much literature has explored how sustainability might be achieved through firms’ internal research and development, and supply chain collaboration. However, issues such as how different stakeholders including customers, partners, government, and universities can be involved, forming innovation ecosystem in a sustainable way is under-explored. This paper aims to provide connection between innovation and sustainability, through literature review and exploratory case studies. A conceptual framework is generated starting from firm/intra-firm level, to supply chain/inter-firm level, and towards ecosystem level. With emerging themes of innovation from sustainability perspective proposed, the framework can be enriched and validated through future empirical studies.

Description: The millennial generation plays a leading role in today’s connected world in which exists a confluence of numerous technologies and the internet in science, economy and innovation. This study aimed to identify the key factors that characterize the millennial generation within the online chatter on Twitter using an innovative approach. To this end, we analyzed the user generated content (UGC) in the social network (SNS) Twitter using a three-steps knowledge-based method for information management. In order to develop this method, we first used latent Dirichlet allocation (LDA), a state-of-the-art thematic modeling tool that works with Python, to analyze topics in our database. The data were collected by extracting tweets with the hashtag #Millennial, #Millennials and #MillennialGeneration on Twitter (n = 35,401 tweets). Secondly, sentiment analysis with a support vector machine (SVM) algorithm was also developed using machine-learning. Applying this method to the LDA results resulted in the categorization of the topics into those that contained negative, positive and neutral sentiments. Thirdly, in order to gather the final results, data text mining techniques were used. The negative factors that characterize the behavior of this generation are depression, loneliness and real-world relationship. The positive factors are body image, self-expression, travelers and digital life and the neutral factors are self-identity and anxiety. Practical implications can be used by public actors, companies or policy makers that are focused on the millennial generation as a target. The study has important theoretical applications as the topics discovered can be used to test quantitative models based on the findings and insights extracted from the UGC sample.

Description: Rigorous peer-review is the corner-stone of high-quality academic publishing [...]

Description: The diffusion of the New Public Management philosophy determines an increasing innovation in the public field. The need for open innovation management is relevant to improve and also increase performance in healthcare organizations. Moreover, this is strictly connected with an efficient accounting and information system able to process, store and share data. Through an inductive approach to the consideration of needs, this paper deals with the social open innovation theory, the innovation of cycle theory, and the microcosting approach. Our analysis allows us to create a new framework which includes both theories and provides results for health managers and health decision-makers.

Description: Small- and medium-sized enterprises (SMEs) in Bangladesh have been growing for the preceding two decades in various ways. Even though these enterprises exert an important effect on the national economy of the country, they face certain challenges and suffer in quite a manner. To reduce the suffering and help deal with these unavoidable challenges, SME foundations in Bangladesh have been working a lot to assist these enterprises. Usually, the challenges are financial, regulatory, or innovation performance-related. Since the enterprises are focused on particular products and their manifestation and production, performing innovatively within these organizations becomes quite a constraint factor. In this paper, a qualitative method was applied with soft systems, where an innovation model was commenced to reduce the challenges and constraints of SMEs in Bangladesh. From the literature, 50 articles were analyzed, a content and thematic analysis was done, and eight main challenges were highlighted and finalized. On the other hand, a focus group discussion among 10 entrepreneurs in Bangladesh was done, where collected data were stored in the NVIVOMac tool, transcribed, and coded, and 55 open codes were identified. These open codes were transferred to 20 axial codes and 8 themes to construct a conceptual innovation model for SMEs in Bangladesh by applying soft systems techniques to connect the themes to each other.

Description: Increasing demand for various social services in accordance with the global social change in time requires a systematic and efficient system based on a user-oriented policy operation method beyond an administrative operation method of social services. Therefore, this study aimed to present a specific direction for the development of the social service system by empirically deriving and discussing the critical factors that can lead to sustainable success of the social service system. To this end, 12 factors in 3 areas were critically analyzed through a questionnaire survey and analysis on the basis of the Analytic Hierarchy Process (AHP) method for the social service workers and users of the 50 Plus Foundation, an organization that helps the elderly in Seoul to continue their social participation. The analysis results confirmed that the service delivery system was the most important factor among the service delivery system, service administration, and service network, and, in particular, factors for users’ active system access, such as accessibility and participation possibility, were the most influential factors for sustainable success of the social service system. Ultimately, unlike in the past, system development and direction should be sought by considering service users rather than a one-sided policy approach of the government for the development and operation of the social service system.

Description: The purpose of this study is to identify the difference in firm performance and employment growth between successful and failed capital procurement through equity-based crowdfunding. We conduct an empirical analysis using entire crowdfunding projects that attempted to raise capital through equity-based crowdfunding in South Korea in 2016. We summarize our findings as follows. Descriptive statistics show that the survival rate, sales growth rate, profitability growth, absolute employment growth, and employment growth rate of companies with successful crowdfunding are higher than those of companies with failed crowdfunding. However, from the difference analysis, we do not find a significant difference in the survival rate, sales growth rate, and profitability growth between companies with crowdfunding success and companies with crowdfunding failure. We find that the absolute employment growth and employment growth rate are significantly higher for companies that succeeded in crowdfunding projects compared to companies that did not. In this study, we find that the characteristics of these firms that are conducting or verifying new projects through equity-based crowdfunding financing are similar to those of prior studies results confirming the short-term effects of entrepreneurial activities or new business activities on economic performance and employment growth. In particular, it is very meaningful to confirm that the direct effect of employment growth is also found in start-up firms that raise capital through equity-based crowdfunding. By investigating the difference in firm performance and employment outcomes according to the results of equity-based crowdfunding investment, this study provides useful insights to investors for their efforts to validate participation in crowdfunding. Also, our study raises important policy implications for regulators in their efforts to resolve unemployment and the lack of capital problem for startups and new businesses.

Description: Western economies nowadays are confronted with a predicted productivity slowdown resulting in diminishing rates of economic growth. While some scholars see these developments as an indication of the approaching end of growth due to fully exploited technological opportunities, this article contends that the possibilities for radical, paradigm changing innovations are far from being exploited. Building on contributions from Schumpeter and Georgescu-Roegen, we argue that the human capacity to expand technological and intellectual frontiers must not be underestimated. In a selective retrospect, our narrative identifies and describes four historical incidents reflecting different perceptions of the power of the human mind. It synthesizes the mentioned economists’ viewpoints with the effects of these incidents to reproduce the intellectual roots of the recently developed concept of Dedicated Innovation Systems (DIS). We conclude that traditional macro-level indicators are not suitable to capture transformation processes, which is why we propose to interpret growth indicators and the alleged productivity slowdown quite differently. We argue that human ingenuity and transformation processes dedicated to sustainability will open up new opportunity spaces, thereby combining an increase in economic welfare and social justice with a reduction of negative environmental impact.

Description: Maintaining a consistently trending portfolio of complements is vital to sustaining platform leadership. Prior research has highlighted the value of open innovation, but has largely disregarded the strategic identification and management of distinctive complements that drive extended platform value, particularly via platform policy modifications. The relevance of prior research around influential policies such as refund leniency becomes largely irrelevant once applied to platform conditions. Utilizing Steam as the medium of analysis, this paper distinguishes complements into three classifications of sustainability, representing its contribution to developing platform leadership. Steam’s refund policy alteration is investigated for its effects on refund revenue reductions and additional demand on each classification, assessed using an indirectly related linear regression between playtime distribution and game age, and a binomially distributed t-test on the percentage of favorable games. The results reveal that, while all patterns experience significant volumes of refunds, corresponding revenue enhancements are perceived only among unsustainable games. This creates a disadvantageous foundation for high-value complements and consequently, an unforeseen disincentive for association, potentially inciting preferential linkage with competitors. This paper further proposes a precedent for future open innovation and platform management research, where complements of highest relevance are identified and granted heightened priority to protect their sustainability.

Description: In the era of economic globalization, small and medium enterprises (SMEs) are recognized as an engine of sustainable economic development in both the developed and developing world. In literature, three competitive challenges—the sustainability challenge, the global challenge and the technological challenge—faced by industrial entities in the current globalized economy, are categorized. Of them, this paper undertakes a systemic review of the literature covering the theme of SMEs and technology in order to identify how technological progress in the SMEs, correlates with SMEs survival improvement in the global competition. The review identified six driving forces—social capital, link with Multi-National Corporations (MNCs) and Transnational Corporations (TNCs), innovation, sharing and networking, information technology, and adoption of productivity-enhancing technology—influencing technological upgrade in the SMEs. The review also identified two conditions for successful technological adaptation in the SME sector—availability of technologically skillful workforce in the economy, and identification of opportunities of new technologies in the competition. These conditions could be viewed in the macro environment and emphasize the need for the economies’ readiness towards SMEs’ success.

Description: Non-ferrous metals are widely used as basic materials in various industrial fields, and zinc is a metal that is produced and used next to iron, aluminum, and copper. In this study, DEA (data envelopment analysis) was applied to measure the efficiency of 43 zinc smelters in three countries in East Asia: Korea, China, and Japan. The constant returns to scale (CRS) and the variable returns to scale (VRS) models, and the slack-based measure (SBM) were used for the analysis. As a result of the efficiency analysis, there were three efficient zinc smelters in the CRS model, 14 in the VRS model and 14 in the SBM. The average efficiency was 0.458 based on the SBM, which indicates that there is room for improvement in efficiency. In addition, the average scale efficiency value was 0.689, showing the scale to be inefficient. Therefore, it can be seen that the labor cost and the energy cost must be brought to an appropriate level. The Tobit regression analysis was used to analyze the causes of efficiency. The greater the capacity and the larger amount of bonus Zn of the refinery, the higher the efficiency of the refinery.

Description: Although there is a rich debate about entrepreneurship and its impact on economic development, much less is known about the actual levels of entrepreneurial activity. The main aim of the article is, thus, to map the level of entrepreneurial activity in the Czech Republic, its structure, and development during the years 2005–2017. The study is based on the secondary data obtained from national structural business statistics, the Global Entrepreneurship Monitor, and the Labour Force Survey. The average rate of entrepreneurial activity in the Czech Republic was 15.2% of the economically active population aged 15–64 years during the analysed period. The activity is dominated by solo-self-employed workers (own-account workers). Job creators represent only 3.2% of the economically active population. Patterns and cohorts of entrepreneurs were identified regarding gender, age, and education. There were 2.5 times more self-employed males compared to females for the past years, and the proportion of job creators is also higher for males. The Czech job creators are on average older (mostly represented in age cohort 40–49 years) compared to solo-self-employed (mainly represented in age cohort 35–44 years) and they have obtained tertiary education to a larger extent. Classification and monitoring of the Czech entrepreneurial activity might serve as an overview for Czech policymakers and regional scholars. Especially from a job creation perspective, it might be very relevant to understand the characteristics of those individuals who employ other workers, aside from themselves. From an international perspective, this study might serve as an inspiration to shed more light on the national levels of entrepreneurship and self-employment.

Description: This study aims to investigate the effects of product and process innovations on manufacturing firm performance in Southeast Asian emerging markets. To this end, using a cross-national sample of 2324 manufacturing firms from the World Bank Enterprise Survey (WBES) dataset of 2015, we test the effects of product and process innovations on the sales growth of manufacturing firms in Vietnam, Malaysia, and Indonesia. This study finds that product innovation is positively related to sales growth while new operating technologies are negatively associated with sales growth. For high-tech firms, product innovation is positively related to sales growth. The findings imply that in Southeast Asian emerging markets, governments and manufacturing firms can enhance performance by investing in product innovation.

Description: Several studies have highlighted the importance of parent–teacher collaboration (PTC) in special education (SE). In Lebanon, there is a widespread perception among practitioners that out of many educational challenges facing SE organizations, there is the need to consolidate successful parent–teacher partnerships. We contribute to research on PTC by applying a conceptual framework from complexity science to investigate the interaction between teachers and parents in one SE organization in Lebanon. The interaction between teachers (internal agents) and parents (external agents) constitute an important dimension of the information flow between the school and its surrounding environment. We follow a narrative approach aiming at grasping the temporal dimension of teachers’ experience related to interacting with parents. Findings from this study indicate that teachers play an important role in sensing educational challenges and reaching out for a collaboration. However, although they gain access to valuable information regarding students’ background and social environment, several organizational factors restrain internal knowledge-sharing and communication about innovative practices. Teachers’ narratives depict learning on an individual level, but organizational barriers in the form of negative feedback loops for knowledge-sharing at the organizational level. This study recommends facilitating adaptive processes deriving from PTC. This demands positive feedback loops that facilitate behavioral variation, open communication, and thereby the exploration of innovative practices.

Description: This study aims to examine the impacts of firm constraints and proactive innovation on firm performance, using a sample of 3504 small and medium enterprises (SMEs) in Vietnam from 2011–2015. Our findings suggest that technological innovations in general are beneficial to firm performance, increasing firm sales and profits. Further filtering innovations into two categories of proactive and reactive ones, we find that reactive innovation negatively affects firm performance, consistent with the view that proactive entrepreneurial behavior is a highly sought-after characteristic or a valuable resource for a firm as specified in resources-based theory. Finally, our result implies that if firms have low constraint or have sufficient resources, proactive strategies should be the choice if firms seek to improve their performance.

Description: As the Korean government expands the budget for national research and development, the need for an institute that deliberates, coordinates, and operates research development and its budget has increased. In response to these demands, the National Science and Technology Council (NSTC) was recently established. However, to achieve a creative economy, which is the economic system where value is based on novel imaginative qualities rather than the traditional resources of land, labor, and capital, more efficiently, fundamental research regarding the current state of the Korean national administration system of science and technology in Korea is required. Accordingly, this study first analyzes the function and organizational structure of the NSTC in Korea. Second, it investigates the current state of the NSTC in other countries. Finally, the study derives several implications for improving NSTC operation based on the benchmarking study and suggests an operational improvement plan for NSTC with respect to enhancement of function, operation of organization, human resource management, and improvement of the relationships between other departments. The study contributes to analyze the current state of the NSTC in Korea and science and technology (S&T) Councils in other major countries, systematically and in detail. In addition, based on benchmarking study, this study derived operational improvement of NSTC in Korea with four perspectives, including enhancement of function, operation of organization, human resource management, and improvement of the relationships between other departments.

Description: Changes in workplace demographics in the oil and gas industry have raised a concern about the risks of a knowledge-loss crisis due to mass retirement. The industry response has often consisted of strategies aimed at mapping knowledge across organizational units, codifying knowledge in databases, and mentoring new staff. However, such common managerial responses show important limitations in terms of grasping tacit and network-based dimensions of knowledge in complex oil production operations. Therefore, there is an industrial need for innovative knowledge management practices. In this conceptual article, we look at the knowledge-loss crisis from the perspective of network resilience in complex systems. A central assumption here is that it is important to look at retiring staff not only in terms of their explicit knowledge, but also in relation to their roles in evolving networks of interactions. Why do some social systems adapt to the departure of some individuals, recover from eventual knowledge-loss crises, and keep performing its functions? From an anticipatory logic, network analysis may show the initial conditions of a system and identify possible loss scenarios. From an adaptive logic, network analysis may inform interventions aimed at facilitating processes of interactions from which new knowledge may emerge and spread. Integrated operations may be a step in this direction.

Description: Digitalization is frequently addressed in recent economic and social scientific literature. This paper applies a distinction to digital data (raw data) and digital technologies (including both software platforms and hardware solutions). The open data is defined as follows: it is publicly available and non-chargeable data (information content) that is machine readable. Open data enables software and application development for external partners and users. A common feature in open-data applications is location-based identification (e.g., real-time traffic monitoring). These include spatial map visualizations, and monitoring of traffic and modes of transport. This visualized information provides additional support for data-based decision-making and management as these study results indicate. This information is valuable particularly in the decisions concerning unconventional and sudden events. This research indicates that the most suitable data resources for opening include information related to port transport infrastructure. In terms of temporal monitoring, static road and rail data is currently the most potential alternative for open data in ports. The main reasons are that these data sources are already at least partly published. However, they are not always in open-data formats. Static data is also a grounded starting point because the technical requirements are much less demanding in comparison to real-time data-processing and management

Description: Culture is a key driving force in enhancing organizational performance. The results of recent studies indicate the importance of managers having the capacity to understand organizational culture and link it to organizational performance improvement. This study aims to examine the relationship between organizational culture and performance improvement in social enterprises. In the past, organizational culture was described in terms of a single dimension, but it is now understood that different cultures reflect different values and beliefs, in a seemingly contradictory manner, and can coexist within any given organization. We analyze the relationships among social enterprise networking, performance, and organizational culture, using the four organizational culture classifications of the competing values framework, which reflects recent perspectives. A survey was conducted among 100 social entrepreneurs, and latent profile analysis was applied to the data. The analytical results identify four latent profiles—namely, strong-balanced, weak-balanced, hierarchical, and group-dominant—and show that a balanced culture fosters high-level socioeconomic performance.

Description: The objective of this study is to summarize the current general evaluation process that stakeholders use to evaluate single or multiple medical devices to select the optimal medical device. This study constructed a novel evaluation framework to select the optimal medical device by overcoming the limitations of assessments that were previously confined to the medical device cycle and the purpose of the specific assessment. It also presents a general framework for incorporating usability evaluations into the frame to reflect the objectives and characteristics of key stakeholders in the medical device industry. In addition, the results of medical device evaluation are further analyzed using the analytical hierarchy process (AHP).

Description: A supporting management discipline is an under researched phenomenon. A majority of firms’ operating capabilities relating to knowledge, innovation and technology management as a supporting management discipline. This paper reviews the literature in the research and development (R&D) domain to formulate and propose a conceptual model which is influenced by capabilities relating to knowledge, innovation and technology management. We performed a systematic literature review in which a range of articles were searched related to R&D, from 1990 to 2018. Our review is presented in two parts. The first part presents a descriptive analysis using the Preferred Reporting Items for Systemic View and Mata Analysis (PRISMA)protocol and the second part develop proposition based on keywords analysis. The review revealed that there are nine capabilities that contribute to influence on R&D based on three dimensions known as knowledge, innovation and technology management which correspond to some of the key resources that used to drive these capabilities. Finally, this work proposes a conceptual model based on the outcome of Systematic Literature Review (SLR) interpretation. This research may support current trends on the literature. The list of references may be considered a potential source for future research in this area.

Description: Despite a growing interest in the effects of arts-based interventions on organizational change, concepts aiming at business innovation and product development other than residencies are rare. Furthermore, little is known about the role and impact of artists involved in idea-generating formats. How does the personal presence of artists in a heterogenous working group influence the procedure? To what extent do artists unfold their creative qualities while dealing with such a non-artistic challenge? The paper introduces a method named Art Hacking that applies professional labour attitudes typical for artists and artistic modes of thinking to business problems and enhances the approach by having artists attend the whole intervention. One of these events was taken as a case for exploring the role of four artists in the collective idea-generation process. The results of participatory observation along critical incident technique substantiate the thesis that in interdisciplinary “playgrounds” artists implicitly become process leaders. They are catalysts for awareness, sensemaking and change of perspective.

Description: The role of venture capital as mediator and gatekeeper is well acknowledged and geographical barriers for open innovation have been questioned, but venture capital firms’ distant investments have been investigated only rarely. The strategic benefits accrued from corporate venture capital (CVC) investment depend on the selection of target ventures. Prior research, however, overlooked the incurred information cost for identifying a potential target. Considering that innovative ventures often reside in distant locations, this paper aims to investigate what factors alleviate the information cost for CVCs when identifying target ventures in distant locations. We expect a CVC’s target selection in distant locations will be limited to the ventures under a tight appropriability regime, ventures within the same industries as a CVC’s business units, and ventures with pre-existing investors that a CVC has prior ties with. The hypotheses are tested with the data on CVC investments in the U.S. between 2006 and 2013. The results empirically support the hypotheses.

Description: In the last few years, the monstrous fan has gained attention in this country for large space buildings and areas. The continuity of this product technology is important to allow it to be able to survive in the current and future market. However, there are limited studies on the present and future scenario of the monstrous fan, especially in Malaysia. Thus, the objective of this paper is to forecast its present technology, evaluating the market demand and future of the monstrous fan. For these reasons, an online survey was used to obtain feedback from suppliers and manufacturers to forecast the future of this product. In conclusion, the monstrous fan has been discussed and predicted, which can be beneficial for various parties including policy makers, government, business and technology players by representing a specific knowledge on the technical specificities of monstrous fans in Malaysia.

Description: Public R and D management agencies have been taking on key roles in the national R and D ecosystem. The purpose of this study is to suggest ways to improve the operational efficiency of public R and D management agencies based on analysis of their current status. We approached this study from a life-cycle perspective as it applies to the plan-management evaluation of R and D. Data-collection sources included documents, surveys, and interviews with staff members in agencies responsible for national R and D management. Based on the analysis results, we present suggestions for improvement in three areas: (a) unification of R and D planning and evaluation of individual ministries; (b) establishment of a panministerial management system for public R and D management agencies; (c) improvement and development of public R and D agencies’ expertise and management services. Finally, we discuss possible improvements and the limits of this study.

Description: Open source software and open innovation are an important resource for today’s industries. Communities collaboratively create different kind of publicly available value, boosting innovation and also technology. However, whereas this value is generated and captured by various involved parties, the outcomes are, in many cases, commercialized by companies who build their business models on this openness. Thus, current business model representations used for these open systems mainly focus on the commercial side of companies, not directly regarding the value creation and distribution by the underlying communities. This results in a lack of potential representation of alternative value created by individuals and communities that are not necessarily aiming for direct monetary compensation. In this work, we show, by the example of open source projects, how communities create value and their potential to be represented by the upcoming domain of new business models. The emerging idea of new business models, based on sharing, collaboration, and the circular economy, not only considers economical viewpoints, but also social and ecological. New trends in research are intensively starting to investigate these models and how they can be brought to practice. The co-creation of value, collaboration of various actors, and following a shared vision are just some of the identified overlaps that are also essential for a potential representation of open communities. This first review unveils that new business models and open source software projects have a variety of aspects in common. We highlight the potential of open communities to be seen as new business models themselves, instead of just being a pure enabler for firms’ business models. This approach is leaving room to explore new organizational and economical aspects of open ecosystems, enhancing the understanding of co-creative communities and the definition of collaborative value.

Description: The constant increase of municipal solid wastes (MSW) as well as their daily management pose a major challenge to European countries. A significant percentage of MSW originates from household activities. In this study we calculate the costs of setting up and running a zero-waste mortar-producing (ZWMP) process utilizing MSW in Northern Greece. The process is based on a thermal co-processing of properly dried and processed MSW with raw materials (limestone, clay materials, silicates and iron oxides) needed for the production of clinker and consequently of mortar in accordance with the Greek Patent 1003333, which has been proven to be an environmentally friendly process. According to our estimations, the amount of MSW generated in Central Macedonia, Western Macedonia and Eastern Macedonia and Thrace regions, which is conservatively estimated at 1,270,000 t/y for the year 2020 if recycling schemes in Greece are not greatly ameliorated, may sustain six ZWMP plants while offering considerable environmental benefits. This work can be applied to many cities and areas, especially when their population generates MSW at the level of 200,000 t/y, hence requiring one ZWMP plant for processing.

Description: Network-on-chip (NoC) based system-on-chips (SoC) has been a promising paradigm of core-based systems. It is difficult and challenging to test the individual Intellectual property IP cores of SoC with the constraints of test time and test power. By reusing the on-chip communication network of NoC for the testing of different cores in SoC, the test time and test cost can be reduced effectively. In this paper, we have proposed a power-aware test scheduling by reusing existing on-chip communication network. On-chip test clock frequencies are used for power efficient test scheduling. In this paper, an integer linear programming (ILP) model is proposed. This model assigns different frequencies to the NoC cores in such a way that it reduces the test time without crossing the power budget. Experimental results on the ITC’02 benchmark SoCs show that the proposed ILP method gives up to 50% reduction in test time compared to the existing method.

Description: This paper proposes a modularity for paralleling different rated power supplies without adding a circuit in the feedback loop by using direct and overlapped switching methods. Unlike an isolated output diode, the use of an isolated output switch composed of two Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) can reduce power dissipation. The control module includes switches and a micro-programmed controlled unit that realizes the modularity by using multi-phase switching methods. The proposed module was studied, and experiments of two rated power supplies (60 and 45 W) were conducted to verify the studied results.

Description: With the ever-increasing industrial demand for bigger, faster and more efficient systems, a growing number of cores is integrated on a single chip. Additionally, their performance is further maximized by simultaneously executing as many processes as possible. Even in safety-critical domains like railway and avionics, multicore processors are introduced, but under strict certification regulations. As the number of cores is continuously expanding, the importance of cost-effectiveness grows. One way to increase the cost-efficiency of such a System on Chip (SoC) is to enhance the way the SoC handles its power consumption. By increasing the power efficiency, the reliability of the SoC is raised because the lifetime of the battery lengthens. Secondly, by having less energy consumed, the emitted heat is reduced in the SoC, which translates into fewer cooling devices. Though energy efficiency has been thoroughly researched, there is no application of those power-saving methods in safety-critical domains yet. The EU project SAFEPOWER (Safe and secure mixed-criticality systems with low power requirements) targets this research gap and aims to introduce certifiable methods to improve the power efficiency of mixed-criticality systems. This article provides an overview of the SAFEPOWER reference architecture for low-power mixed-criticality systems, which is the most important outcome of the project. Furthermore, the application of this reference architecture in novel railway interlocking and flight controller avionic systems was demonstrated, showing the capability to achieve power savings up to 37%, while still guaranteeing time-triggered task execution and time-triggered NoC-based communication.

Description: The main challenge in designing a loop filter for a phase locked loop (PLL) is the physical dimensions of the passive elements used in the circuit that occupy large silicon area. In this paper, the basic features of a charge-controlled memristor are studied and the design procedures for various components of a PLL are examined. Following this, we propose a memristor-based filter design which has its resistance being replaced by a memristor in order to reduce the die area and achieve a low power consumption. We obtained a tuning range of 741–994 MHz, a stable output frequency of 1 GHz from the transfer characteristics of voltage-controlled oscillator (VCO), and an improved settling time. In addition to reduced power consumption and area occupied on the chip, our design shows a high reliability over wider range of temperature variations.

Description: This paper describes an innovative solution for the power supply of a fast field cycling (FFC) nuclear magnetic resonance (NMR) spectrometer considering its low power consumption, portability and low cost. In FFC cores, the magnetic flux density must be controlled in order to perform magnetic flux density cycles with short transients, while maintaining the magnetic flux density levels with high accuracy and homogeneity. Typical solutions in the FFC NMR literature use current control to get the required magnetic flux density cycles, which correspond to an indirect magnetic flux density control. The main feature of this new relaxometer is the direct control of the magnetic flux density instead of the magnet current, in contrast with other equipment available in the market. This feature is a great progress because it improves the performance. With this solution it is possible to compensate magnetic field disturbances and parasitic magnetic fields guaranteeing, among other possibilities, a field control below the earth magnetic field. Experimental results validating the developed solution and illustrating the real operation of this type of equipment are shown.

Description: One of the most widely accepted explanations for why wars occur despite its Pareto-suboptimality is mutual optimism: if both sides expect to gain a lot by fighting, war becomes inevitable. The literature on mutual optimism typically assumes mutually optimistic beliefs and shows that, under such an assumption, war may occur despite its Pareto-suboptimality. In a war–peace model, we show that, if players neglect the correlation between other players’ actions and their types—a well-established concept in economics—then players’ expected payoffs from war increase relative to conventional informational sophistication predictions, hence providing a microfoundation of mutual optimism.

Description: Inspired by the work of Rubinstein, this study revisits data from a previous lab experiment to explore the relation between response times and tax compliance and understand the potential non-linearity between them by classifying decisions and individuals into compliance types. We find that individuals’ decision response time is related to their compliance decisions. Full-non compliant individuals (those who did not declare any earned income) have shorter response times than those who fully or partially complied. Full-compliant individuals also tend to declare income faster than partially compliant subjects. Such results are robust throughout time and when controlling for contextual characteristics of experimental design. We find non-linearity via an inverted U-shape function that reaches its maximum declaration time around a compliance rate of 60%, even after controlling for contextual experimental design factors. In addition, we observe a non-linear relation between cognitive skills, response time, and tax compliance. Participants with relatively high cognitive skills and very low or very high tax compliance level have low response times, while subjects with relatively lower cognitive skills tend to report higher decision times for higher compliance levels.

Description: The problem of the existence of Berge equilibria in the sense of Zhukovskii in normal-form finite games in pure and in mixed strategies is studied. The example of a three-player game that has Berge equilibrium neither in pure, nor in mixed strategies is given.

Description: Game spaces in which an organism must repeatedly compete with an opponent for mutually exclusive outcomes are critical methodologies for understanding decision-making under pressure. In the non-transitive game rock, paper, scissors (RPS), the only technique that guarantees the lack of exploitation is to perform randomly in accordance with mixed-strategy. However, such behavior is thought to be outside bounded rationality and so decision-making can become deterministic, predictable, and ultimately exploitable. This review identifies similarities across economics, neuroscience, nonlinear dynamics, human, and animal cognition literatures, and provides a taxonomy of RPS strategy. RPS strategies are discussed in terms of (a) whether the relevant computations require sensitivity to item frequency, the cyclic relationships between responses, or the outcome of the previous trial, and (b) whether the strategy is framed around the self or other. The negative implication of this taxonomy is that despite the differences in cognitive economy and recursive thought, many of the identified strategies are behaviorally isomorphic. This makes it difficult to infer strategy from behavior. The positive implication is that this isomorphism can be used as a novel design feature in furthering our understanding of the attribution, agency, and acquisition of strategy in RPS and other game spaces.

Description: In experiments of decision-making under risk, structural mixture models allow us to take a menu of theories about decision-making to the data, estimating the fraction of people who behave according to each model. While studies using mixture models typically focus only on how prevalent each of these theories is in people’s decisions, they can also be used to assess how much better this menu of theories organizes people’s utility than does just one theory on its own. I develop a framework for calculating and comparing two kinds of rationalizable opportunity cost from these mixture models. The first is associated with model mis-classification: How much worse off is a decision-maker if they are forced to behave according to model A, when they are in fact a model B type? The second relates to the mixture model’s probabilistic choice rule: How much worse off are subjects because they make probabilistic, rather than deterministic, choices? If the first quantity dominates, then one can conclude that model a constitutes an economically significant departure from model B in the utility domain. On the other hand, if the second cost dominates, then models a and B have similar utility implications. I demonstrate this framework on data from an existing experiment on decision-making under risk.

Description: A standard result of coalition formation games is that stable coalitions are very small if the coalition plays Nash vis-à-vis the rest of the world and if abatement costs are quadratic. It has been shown that larger coalitions and even the grand coalition are possible if the marginal abatement cost is concave. The paper confirms this result, but shows that abatement activities by large coalitions smaller than the grand coalition can be very small. This can be ‘repaired’ only by assuming that the marginal abatement cost curve changes its curvature extremely once the stable coalition has been reached.

Description: In this paper, lab experiments on tax compliance were theoretically investigated with dynamic and stochastic methods. It is well known from experimental games that learning allows a better understanding of participants’ behavior. However, it has not been explicitly applied so far in the theoretical analysis of tax compliance experiments. In this paper, it was shown that two decision-making processes may be distinguished: a discrete process in which all options are regarded and an all-or-nothing process in which either the respective tax is paid fully or not at all. The corresponding variant of the learning model was either a stochastic or a deterministic one, with the stochastic version as the more general model. In the additional empirical part of the paper, it was shown that tax payments decline in trend over the rounds of the considered experiment. This negative trend was interpreted as a learning effect, in accordance with the stochastic version of the theoretical model. However, the alternative interpretation that the observed behavior was driven by a tiring effect cannot be completely excluded.

Description: Since social dilemmas among n-persons are often embedded in other types of social exchanges, the exclusion of defectors in social dilemmas from other exchanges functions as a costless selective incentive. Recently, such “linkage” has been considered as a promising solution to resolve the social dilemma problem. However, previous research showed that cooperation sustained by linkage is fragile when subjective perception errors exist. The purpose of this study is to find linkage strategies that are robust against subjective perception errors. Based on the strategies presented in previous studies on indirect reciprocity, we devised several linkage strategies and examined their evolutionary stability by agent-based simulation. The simulation results showed that the linkage strategy based on kandori was evolutionarily stable even when perception errors existed. Our study provides substantial support for the argument that linkage is a plausible solution to the social dilemma problem.

Description: A game-theoretic model of repeated interaction between two potential adversaries is analyzed to illustrate how conflict could possibly arise from rational decision-makers endogenously processing information, without any exogenous changes to the fundamentals of the environment. This occurs as a result of a convergence of beliefs about the true state of the world by the two players. During each period, each adversary must decide to either stage an attack or not. Conflict ensues if either player chooses to initiate an attack. Choosing to not stage an attack in a given period reveals information to the player’s rival. Thus, over time, beliefs about the true state of the world converge. Depending upon the true state of the world, we can ultimately have either of the two adversaries initiating an attack (either with or without regret) after an arbitrarily long period of tranquility. When this happens, it is as if conflict has suddenly arisen without any apparent cause or impetus. Alternatively (again, depending upon the true state of the world), we could possibly have beliefs converge to a point where neither adversary wants to initiate conflict.

Description: A stylized fact from laboratory experiments is that there is much heterogeneity in human behavior. We present and demonstrate a computationally practical non-parametric Bayesian method for characterizing this heterogeneity. In addition, we define the concept of behaviorally distinguishable parameter vectors, and use the Bayesian posterior to say what proportion of the population lies in meaningful regions. These methods are then demonstrated using laboratory data on lottery choices and the rank-dependent expected utility model. In contrast to other analyses, we find that 79% of the subject population is not behaviorally distinguishable from the ordinary expected utility model.

Description: We consider the problem of sharing the cost of connecting a large number of atomless agents in a network. The centralized agency elicits the target nodes that agents want to connect, and charges agents based on their demands. We look for a cost-sharing mechanism that satisfies three desirable properties: efficiency which charges agents based on the minimum total cost of connecting them in a network, stand-alone core stability which requires charging agents not more than the cost of connecting by themselves directly, and limit routing-proofness which prevents agents from profitable reporting as several agents connecting from A to C to B instead of A to B. We show that these three properties are not always compatible for any set of cost functions and demands. However, when these properties are compatible, a new egalitarian mechanism is shown to satisfy them. When the properties are not compatible, we find a rule that meets stand-alone core stability, limit routing-proofness and minimizes the budget deficit.

Description: We design an experiment to test how voters vote in a small committee election with three alternatives. Voters have common preferences that depend on an unknown state of nature. Each voter receives an imprecise private signal prior to the election and then casts a vote. The alternative with the most votes wins. We fix the number of voters in our experiment to be five and focus on differences in the information structure (prior and signal distributions). We test three different treatments (different prior and signal distributions) that pose different challenges for the voters. In one, simply voting for one’s signal is an equilibrium. In the other two, it is not. Despite the different levels of complexity for the voters, they come relatively close to the predicted strategies (that sometimes involve mixing). As a consequence, the efficiency of the decision is also relatively high and comes close to predicted levels. In one variation of the experiment, we calculate posterior beliefs for the subjects and post them. In another, we do not. Interestingly, the important findings do not change.

Description: Mutation-generated variation in behavior is thought to promote the evolution of cooperation. Here, we study this by distinguishing two effects of mutation in evolutionary games of the finitely repeated Prisoner’s Dilemma in infinite asexual populations. First, we show how cooperation can evolve through the direct effect of mutation, i.e., the fitness impact that individuals experience from interactions with mutants before selection acts upon these mutants. Whereas this direct effect suffices to explain earlier findings, we question its generality because mutational variation usually generates the highest direct fitness impact on unconditional defectors (AllD). We identify special conditions (e.g., intermediate mutation rates) for which cooperation can be favored by an indirect effect of mutation, i.e., the fitness impact that individuals experience from interactions with descendants of mutants. Simulations confirm that AllD-dominated populations can be invaded by cooperative strategies despite the positive direct effect of mutation on AllD. Thus, here the indirect effect of mutation drives the evolution of cooperation. The higher level of cooperation, however, is not achieved by individuals triggering reciprocity (‘genuine cooperation’), but by individuals exploiting the willingness of others to cooperate (‘exploitative cooperation’). Our distinction between direct and indirect effects of mutation provides a new perspective on how mutation-generated variation alters frequency-dependent selection.

Description: Refinements of the Nash equilibrium have followed the strategy of extending the idea of subgame perfection to incomplete information games. This has been achieved by appropriately restricting beliefs at unreached information sets. Each new refinement gives stricter and more mathematically-complicated limitations on permitted beliefs. A simpler approach is taken here, where the whole idea of beliefs is dispensed with, and a new equilibrium concept, called the ideal reactive equilibrium, that builds on some pioneering work by Amershi, Sadanand and Sadanand on thought process dynamics, is developed.

Description: I investigate how different dispersal patterns affect the evolution of cooperation in a spatially-structured population. I consider a finite fixed-size population of cooperators and free-riders residing on a one-dimensional lattice with periodic boundaries. Individuals interact via a multiplayer game, which is a version of a public goods game, and the population evolves via a Moran process. Individuals try to improve their interactions by evaluating the current state of the environment and moving to locations with better payoffs. I ran stochastic simulations of the evolution of this Markov process and found that if individuals disperse deterministically to locations with the best payoffs, then cooperation can still be maintained even in the worst-case scenarios, albeit at reduced levels compared to the better-case scenarios. This contrasts with an earlier investigation of probabilistic dispersal patterns, which resulted in the breakdown of cooperation in sparse populations with small interaction neighborhoods, a high mobility rate, and a large dispersal range.

Description: Rigorous peer-review is the corner-stone of high-quality academic publishing [...]