A Dynamic Model of Decision-making in the IS/IT Outsourcing Process: A Case Study from a Government-supported

The IS/IT outsourcing process is complex and the outcome is unpredictable, especially in the varied participants, complicated social and political environments. Prior research on IS/IT outsourcing decisions simply assumed the rational, comprehensive, independent decisionmaking activity is not descriptively accurate and perhaps thus cannot be prescriptively useful in this complex environment. To get deeper understandings of the decision-making in the IS/IT outsourcing process, this research creates a dynamic model to illustrate the complex phenomenon. In-depth case study methodology and process-oriented analysis strategy were used to interpret a government-supported, outsourced IS project. This study indicates that decision makers should regard the IS/IT outsourcing process as a continuous, integral process in context and consider the structural influence, antecedent conditions, and future impact in every decision episode. This paper provides an initial insight by studying IS/IT outsourcing decision-making through dynamic and process perspective

An Examination of the Relationships among Budget Emphasis, Budget Planning Models and Performance

[[abstract]]Purpose – This study aims to investigate the relationships among budget emphasis, budget planning models, and performance, to determine whether an emphasis on the budget has indirect effects on performance, in the presence of other budget planning characteristics as mediators. Design/methodology/approach – A questionnaire survey was conducted and structural equation modeling was used to test the proposed models among the constructs and related hypotheses. Findings – The results indicate that while budget planning models entirely mediate the influence of budget emphasis on the performance of management and the organization, they partially mediate the influence of budget emphasis on budget satisfaction. In addition, it is determined that differentiation strategies have a significantly positive influence on budget emphasis, budget planning models and performance. Originality/value – The results of this study provide a reference for organizations in the design of budgeting systems. During the design process, budget planning models should consider the degree of emphasis an organization places on the budget.[[incitationindex]]SSCI[[booktype]]紙

Tuning the Solubility of Copper Complex in Atom Transfer Radical Self-Condensing Vinyl Polymerizations to Control Polymer Topology via One-Pot to the Synthesis of Hyperbranched Core Star Polymers

In this paper, we propose a simple one-pot methodology for proceeding from atom transfer reaction-induced conventional free radical polymerization (AT-FRP) to atom transfer self-condensing vinyl polymerization (AT-SCVP) through manipulation of the catalyst phase homogeneity (i.e., CuBr/2,2'-bipyridine (CuBr/Bpy)) in a mixture of styrene (St), 4-vinyl benzyl chloride (VBC), and ethyl 2-bromoisobutyrate. Tests of the solubilities of CuBr/Bpy and CuBr2/Bpy under various conditions revealed that both temperature and solvent polarity were factors affecting the solubility of these copper complexes. Accordingly, we obtained different polymer topologies when performing AT-SCVP in different single solvents. We investigated two different strategies to control the polymer topology in one-pot: varying temperature and varying solvent polarity. In both cases, different fractions of branching revealed the efficacy of varying the polymer topology. To diversify the functionality of the peripheral space, we performed chain extensions of the resulting hyperbranched poly(St-co-VBC) macroinitiator (name as: hbPSt MI) with either St or tBA (tert-butyl acrylate). The resulting hyperbranched core star polymer had high molecular weights (hbPSt-g-PSt: Mn = 25,000, Đ = 1.77; hbPSt-g-PtBA: Mn = 27,000, Đ = 1.98); hydrolysis of the tert-butyl groups of the later provided a hyperbranched core star polymer featuring hydrophilic poly(acrylic acid) segments

Machine Learning-based Indoor Positioning Systems Using Multi-Channel Information

The received signal strength indicator (RSSI) is a metric of the power measured by a sensor in a receiver. Many indoor positioning technologies use RSSI to locate objects in indoor environments. Their positioning accuracy is significantly affected by reflection and absorption from walls, and by non-stationary objects such as doors and people. Therefore, it is necessary to increase transceivers in the environment to reduce positioning errors. This paper proposes an indoor positioning technology that uses the machine learning algorithm of channel state information (CSI) combined with fingerprinting. The experimental results showed that the proposed method outperformed traditional RSSI-based localization systems in terms of average positioning accuracy up to 6.13% and 54.79% for random forest (RF) and back propagation neural networks (BPNN), respectively

Machine Learning-based Indoor Positioning Systems Using Multi-Channel Information

The received signal strength indicator (RSSI) is a metric of the power measured by a sensor in a receiver. Many indoor positioning technologies use RSSI to locate objects in indoor environments. Their positioning accuracy is significantly affected by reflection and absorption from walls, and by non-stationary objects such as doors and people. Therefore, it is necessary to increase transceivers in the environment to reduce positioning errors. This paper proposes an indoor positioning technology that uses the machine learning algorithm of channel state information (CSI) combined with fingerprinting. The experimental results showed that the proposed method outperformed traditional RSSI-based localization systems in terms of average positioning accuracy up to 6.13% and 54.79% for random forest (RF) and back propagation neural networks (BPNN), respectively

Multi-Hop Routing Mechanism for Reliable Sensor Computing

Current research on routing in wireless sensor computing concentrates on increasing the service lifetime, enabling scalability for large number of sensors and supporting fault tolerance for battery exhaustion and broken nodes. A sensor node is naturally exposed to various sources of unreliable communication channels and node failures. Sensor nodes have many failure modes, and each failure degrades the network performance. This work develops a novel mechanism, called Reliable Routing Mechanism (RRM), based on a hybrid cluster-based routing protocol to specify the best reliable routing path for sensor computing. Table-driven intra-cluster routing and on-demand inter-cluster routing are combined by changing the relationship between clusters for sensor computing. Applying a reliable routing mechanism in sensor computing can improve routing reliability, maintain low packet loss, minimize management overhead and save energy consumption. Simulation results indicate that the reliability of the proposed RRM mechanism is around 25% higher than that of the Dynamic Source Routing (DSR) and ad hoc On-demand Distance Vector routing (AODV) mechanisms

An Extended Analytic Solution of Combined Refraction and Diffraction of Long Waves Propagating over Circular Island

An analytic solution of long waves scattering by a cylindrical island mounted on a permeable circular shoal was obtained by solving the linear long wave equation (LWE). The solution is in terms of the Bessel function expressed by complex variables. The present solution is suitable for arbitrary bottom configurations described by a power function with two independent parameters. For the case of the paraboloidal shoal, there exists a singular point (α=2) which can be removed using Frobenius series, where α is a real constant. The present solution is reduced to Yu and Zhang’s (2003) solution for impermeable circular shoal. The numerical results show some special features of the combined effect of wave refraction and diffraction caused by a porous circular island. The effect of key parameters of the island dimension, the shoal slope, and permeability on wave scattering was discussed based on the analytic solution

Prioritizing disease candidate genes by a gene interconnectedness-based approach

<p>Abstract</p> <p>Background</p> <p>Genome-wide disease-gene finding approaches may sometimes provide us with a long list of candidate genes. Since using pure experimental approaches to verify all candidates could be expensive, a number of network-based methods have been developed to prioritize candidates. Such tools usually have a set of parameters pre-trained using available network data. This means that re-training network-based tools may be required when existing biological networks are updated or when networks from different sources are to be tried.</p> <p>Results</p> <p>We developed a parameter-free method, interconnectedness (ICN), to rank candidate genes by assessing the closeness of them to known disease genes in a network. ICN was tested using 1,993 known disease-gene associations and achieved a success rate of ~44% using a protein-protein interaction network under a test scenario of simulated linkage analysis. This performance is comparable with those of other well-known methods and ICN outperforms other methods when a candidate disease gene is not directly linked to known disease genes in a network. Interestingly, we show that a combined scoring strategy could enable ICN to achieve an even better performance (~50%) than other methods used alone.</p> <p>Conclusions</p> <p>ICN, a user-friendly method, can well complement other network-based methods in the context of prioritizing candidate disease genes.</p

Assessing the Green Value Chain to Improve Environmental Performance: Evidence from Taiwan’s Manufacturing Industry

[[abstract]]Purpose – The purpose of this paper is to investigate the relationship between green management and environmental performance. This was accomplished by considering each operational element, including the supply and acquisition of upstream materials, research and development, manufacturing and packaging, marketing, promotion and education, and recycling activities. Design/methodology/approach – The paper constructs an integral model of the green value chain to reveal the extent to which Taiwanese manufacturing industries are adopting green value chain management and implementing environmentally conscious business practices. Survey data were collected from 118 Taiwanese manufacturers. Findings – The findings indicate a positive relationship between green value chain management and environmental performance. The results suggest that when firms only implement green management in particular areas the effect is insignificant; however, a comprehensive implementation can result in an overall improvement in environmental performance. Originality/value – This paper may serve as a reference for firms mapping out future environmental policies and provide an input of various perspectives and arguments into the discipline of green management.[[notice]]補正完畢[[journaltype]]國外[[booktype]]紙本[[countrycodes]]GB