• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.909-916
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• 2021

The purpose of the research to analyze SMEs' technological innovation performance in the Special Region of Yogyakarta based on green supply chains. This study's technology innovation performance is influenced by environmental management practices, green supply chain integration, and supply chain knowledge-sharing. This research is important because many SMEs are underdeveloped in terms of technology innovation performance. Technology innovation performance shows that innovation has a multi-dimensional ecological performance in organizations. Therefore, SMEs' sustainable supply chain could be achieved by managing operations, support, and information by focusing on environmental and social issues to maximize the entire chain. This study used primary data. The number of respondents in this study was 200 SMEs that have implemented green supply chain management practices. The data collection method used was a questionnaire. The data analysis technique tool used is a two-step approach to SEM-AMOS. The results of this study indicate that SMEs are willing to implement a green supply chain to increase their performance. The technological innovation performance model of this study is acceptable. The findings of this research suggest that companies must be encouraged to maintain and increase the implementation of green supply chain integration and better supply chain knowledge-sharing with improved technological innovation performance enhancements.

• The Journal of Information Systems
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• v.30 no.2
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• pp.165-188
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• 2021

Purpose This study was conducted to identify the multidimensional role of institutional mechanisms in the linear relationship of satisfaction, trust and repurchase intention, which are used as an important concept in the research of e-commerce. To this end, a research model was proposed by combining concepts which are the concept of perceived effectiveness of institutional mechanisms for overall e-commerce environment(e.g., PEEIM) and the concep of perceived effectiveness of institutional structures(e.g., PEIS) of a specific marketplace based on the social cognitive theory. Design/methodology/approach This study was conducted by dividing the data into two groups to identify institutional mechanisms and trust-building relationships according to the institutional contexts inherent in e-commerce. The institutional contexts were set up for the top two online companies and the bottom two online companies according to the results of the open market brand assessment from 2018 to 2019 in South Korea. Findings The result of this study found that PEIS had a direct impact on trust in both high and low groups respectively whereas PEEIM presented different paradoxical results in high and low groups. In the relationship between the satisfaction and the trust in the vendor of the high group, PEEIM showed negative moderating effects but in the relationship between the trust and the repurchase intention of the low group PEEIM showed positive moderating effects.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.232-240
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• 2022

To fulfill user expectations, the rapid evolution of software techniques and approaches has necessitated reliable and flawless software operations. Aging prediction in the software under operation is becoming a basic and unavoidable requirement for ensuring the systems' availability, reliability, and operations. In this paper, an improved evolutionary computing-driven extreme learning scheme (ECD-ELM) has been suggested for object-oriented software aging prediction. To perform aging prediction, we employed a variety of metrics, including program size, McCube complexity metrics, Halstead metrics, runtime failure event metrics, and some unique aging-related metrics (ARM). In our suggested paradigm, extracting OOP software metrics is done after pre-processing, which includes outlier detection and normalization. This technique improved our proposed system's ability to deal with instances with unbalanced biases and metrics. Further, different dimensional reduction and feature selection algorithms such as principal component analysis (PCA), linear discriminant analysis (LDA), and T-Test analysis have been applied. We have suggested a single hidden layer multi-feed forward neural network (SL-MFNN) based ELM, where an adaptive genetic algorithm (AGA) has been applied to estimate the weight and bias parameters for ELM learning. Unlike the traditional neural networks model, the implementation of GA-based ELM with LDA feature selection has outperformed other aging prediction approaches in terms of prediction accuracy, precision, recall, and F-measure. The results affirm that the implementation of outlier detection, normalization of imbalanced metrics, LDA-based feature selection, and GA-based ELM can be the reliable solution for object-oriented software aging prediction.

• Journal of Microbiology and Biotechnology
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• v.32 no.12
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• pp.1573-1582
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• 2022

In this study, we investigated the optimal conditions for 3D structure printing of alternative fats that have the textural properties of lard using beeswax (BW)-based oleogel by a statistical analysis. Products printed with over 15% BW oleogel at 50% and 75% infill level (IL) showed high printing accuracy with the lowest dimensional printing deviation for the designed model. The hardness, cohesion, and adhesion of printed samples were influenced by BW concentration and infill level. For multi-response optimization, fixed target values (hardness, adhesiveness, and cohesiveness) were applied with lard printed at 75% IL. The preparation parameters obtained as a result of multiple reaction prediction were 58.9% IL and 16.0% BW, and printing with this oleogel achieved fixed target values similar to those of lard. In conclusion, our study shows that 3D printing based on the BW oleogel system produces complex internal structures that allow adjustment of the textural properties of the printed samples, and BW oleogels could potentially serve as an excellent replacement for fat.

• Geomechanics and Engineering
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• v.35 no.4
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• pp.367-383
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• 2023

The present paper examines the natural frequency responses of the bi-directional (n_x-n_y, n_y-n_z and n_z-n_x) and multidirectional (n_x-n_y-n_z) functionally graded (FG) plate and curved structures with and without porosity. The even and uneven kind of porosity pattern are considered to observe the influence of porosity type and porosity index. The numerical findings have been obtained using a higher order shear deformation theory (HSDT) based isometric finite element (FE) approach generated in a MATLAB platform. According to the convergence and validation investigation, the proposed HSDT based FE model is adequate to predict free vibrational responses of multidirectional porous FG plates and curved structures. Further a parametric analysis is carried out by taking various design parameters into account. The free vibrational behavior of bidirectional (2D) and multidirectional (3D) perfect-imperfect FGM structure is examined against various power law index, support conditions, aspect, and thickness ratio, and for the curvature of curved structures. The results indicate that the maximum non-dimensional fundamental frequency (NFF) value is observed in perfect FGM plates and curved structures compared to porous FGM plates and curved structures and it is maximum for FGM plates and curved structures with uneven kind of porosity than even porosity.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.453-458
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• 2011

The construction industry's importance to nation building, economic empowerment, and contributions to global commerce cannot be over emphasised. However, poor productivity, accidents, rework, time and cost overruns, and client dissatisfaction have characterised the industry performance in a multi-dimensional way. The central issue in this particular research is the seemingly inadequate achievement of optimum performance in the construction process, either with respect to value for money for the client and the entire construction supply chain or value in terms of the utility derived from built assets in spite of efforts by government and governmental bodies such as the Construction Industry Development Board (cidb) to increase industry performance. Therefore, based upon an extensive review of related literature, the paper reports on effects and causes of non-value adding activities in the construction industry in general, and South African construction in particular. The research findings indicate that activities that can be referred to as non-value activities are not only prevalent, but they can also be held responsible for performance related issues in terms of cost, time, quality and health and safety (H&S) in construction; and the exploration of pluralism in the research methodology may result in a robust model based upon the system dynamics approach. Therefore, the study suggests that there is major scope for value optimisation in the construction process especially in terms of availability and implementation of interventions, which have not only proven successful in other industries, but are also adaptable in the construction industry context.

• Information Systems Review
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• v.13 no.3
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• pp.47-63
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• 2011

The rapid spread of the Smartphone usage among the public has brought great changes to the overall society. Aiming to gain their competitiveness with better Smartphone service quality, manufacturers are endeavoring to keep the pace with the popularization of mobile internet and social changes. Researches on the Smartphone service quality are actively undergoing in the academic circles as well. A great many of studies ranging from the past mobile services to the recent Smartphone services have thus far focused on proposing the systematic arrangement and the typology in terms of service quality, which in turn have provided the theoretical foundation and broaden the scope of comprehension. Besides technical aspects of the mobile and Smartphone services, the earlier studies in the behavioral domain, however, only took into considerations the positive aspect of users' satisfaction with the quality of services via new media devices like Smartphone. The rationale behind this mainly comes from the assumption that as the opposite definition of satisfaction is dissatisfaction, the services are not adopted if dissatisfied. However, it is not always true to conclude that service users are satisfied when the service is functionally fulfilled and dissatisfied otherwise. That is because there exist some cases that quality attributes provide satisfaction when achieved fully, but do not cause dissatisfaction when not fulfilled. And there also exist other cases that quality attributes are taken for granted when fulfilled but result in dissatisfaction when not fulfilled. To account this multi-dimensional feature of service quality attributes in relation with user satisfaction, this study took advantage of Kano model following the identification of a set of the Smartphone service quality attributes by investigating the previous studies. Categorizing of the service quality elements reflecting the customers' needs would perhaps help manage Smartphone service quality, enabling business managers to identify which quality attributes more emphasis to put on and what strategy to establish for the future.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.309-327
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• 2021

Dynamic treatment regimes (DTRs) are decision-making rules designed to provide personalized treatment to individuals in multi-stage randomized trials. Unlike classical methods, in which all individuals are prescribed the same type of treatment, DTRs prescribe patient-tailored treatments which take into account individual characteristics that may change over time. The Q-learning method, one of regression-based algorithms to figure out optimal treatment rules, becomes more popular as it can be easily implemented. However, the performance of the Q-learning algorithm heavily relies on the correct specification of the Q-function for response, especially in observational studies. In this article, we examine a number of double-robust weighted least-squares estimating methods for Q-learning in high-dimensional settings, where treatment models for propensity score and penalization for sparse estimation are also investigated. We further consider flexible ensemble machine learning methods for the treatment model to achieve double-robustness, so that optimal decision rule can be correctly estimated as long as at least one of the outcome model or treatment model is correct. Extensive simulation studies show that the proposed methods work well with practical sample sizes. The practical utility of the proposed methods is proven with real data example.

• International Commerce and Information Review
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• v.15 no.1
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• pp.227-256
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• 2013

Existing multinational subsidiary typologies seem to have limitations in two respects. First, the prevalence of subsidiary classification along two-dimensions fails to capture many distinct subsidiary types. Failure to reflect a sufficient richness in dimensionality can give rise to a partial picture of subsidiary typologies in the international business literature. A new typology developed from multi-dimensional approach will be required for reflecting various subsidiary roles in the multinational enterprise. Second, multinational subsidiary performing a number of activities is hard to be defined functionally across the value chain activities. In addition, multinational subsidiary roles can vary dramatically. In conclusion, despite a growing amount of work on subsidiary typologies, there seems to be limited convergence of results. the study regarding subsidiary roles still remain a challenge. In this respect, the purpose of this study is to develop a new typology based on multi-dimensional approach in order to overcome the limitations of traditional typologies. To classify subsidiary types, we propose 8 types of multinational subsidiary according to three dimensions that are adopted: (1) number of required value chain activities (2) subsidiary's sourcing capability and autonomy (3) global orientation (3) The case study analyzing Korean foreign subsidiaries appropriate for 8 types is performed to establish the validity of this study.

• Convergence Security Journal
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• v.21 no.1
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• pp.177-189
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• 2021

Defense R&D is a key process for securing weapons systems determined by mid- and long-term needs to cope with changing future battlefield environments. In particular, the test and evaluation provides information necessary to determine whether or not to switch to mass production as the last gateway to research and development of weapons systems and plays an important role in ensuring performance linked to the life cycle of weapons systems. Meanwhile, if you look at the recent changes in the operational environment of the Korean Peninsula and the defense acquisition environment, you can see three main characteristics. First of all, continuous safety accidents occurred during the operation of the weapon system, which increased social interest in the safety of combatants, and the efficient execution of the limited defense budget is required as acquisition costs increase. In addition, strategic approaches are needed to respond to future battlefield environments such as robots, autonomous weapons systems (RAS), and cyber security test and evaluation. Therefore, in this study, we would like to present strategies for improving the testing and evaluation of weapons systems by considering the characteristics of the security environment that has changed recently. To this end, the improvement strategy was derived by analyzing the complementary elements of the current weapon system operational test and evaluation system in a multi-dimensional model and prioritized through the hierarchical analysis method (AHP).