A Decision-Making Model of Technological-Focused Government Agency Selection of Technological Start-Up Businesses

In developing countries, the government has played an important role in supporting startup businesses in various aspects, primarily through tech-focused government agencies. With a limited budget, the government agencies are critical to select plenty of tech startups for funding, leaving only promising tech startups. Consequently, government agencies inevitably face decision-making problems under uncertain circumstances, like private equity investment situations. Reviewing the relevant decision-making frameworks has identified that a classical multiple criteria decision-making (MCDM) approach is currently used, assuming decision-makers acquire complete information that is not realistic. Moreover, both qualitative and quantitative criteria used in evaluating startup businesses cannot represent the uncertainty which is the fundamental nature of the decision-making circumstance. Thus, this article presents a decision-making framework of tech-focused government agencies for selecting startup businesses based on a fuzzy MCDM of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Besides, it identifies selection criteria with mixed research methodologies and determines weights of importance criteria by the Delphi method. Finally, the proposed framework results are fairness, transparency, and eliminating bias in decision-making, including more efficiency when the framework’s ranking orders significantly correspond with actual performances. HIGHLIGHTS Criteria for selecting start-up businesses in technological-focused government agencies A decision-making framework of tech-focused government agencies for selecting startup businesses based on a fuzzy MCDM of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) The performance of the decision-making framework in selecting startup businesses to acquire high potential tech startups to drive the national economy GRAPHICAL ABSTRACT

Evaluating the Electronic Service Quality of E-Shops Using AHP-TOPSIS

The purpose of this study is to evaluate and rank the e-shops of the top Greek coffee-chains, based on their electronic service quality. Data were collected from experts during the first COVID-19 lockdown. Based on the E-S-QUAL model, we applied a 12-step multi-criteria decision-making methodology utilizing analytic hierarchy process (AHP), and technique for order performance by similarity to ideal solution (TOPSIS). The results indicate that system availability and fulfillment are the two most crucial dimensions of the model. Protection of credit card information, webpages that do not freeze during the ordering process, delivery of the ordered items, and truthfulness about products and services offered by the e-shop are considered the most important sub-dimensions. Our findings can aid managers and practitioners focus on the most important service quality elements when developing e-commerce websites. Furthermore, our study’s results highlight the positive and negative areas of performance of the e-shops under evaluation.

Hydrogen emission in enclosed volume (tunnel for mobility)

Fuel cell vehicles and trains (FCVs) are seen as a viable alternative to fossil fuel-powered vehicles, with the potential to help the automotive and transport industry grow sustainably. Because of their zero emissions, great efficiency, and diverse hydrogen sources, they are an ideal solution to climate change and the global energy issue. In this study, the simulation of releasing hydrogen from a moving vehicle inside a tunnel has been done. For this purpose, two scenarios have been considered. In the first one, it assumed that hydrogen propagates inside a tunnel without ignition and in the second approach, hydrogen released considered to be combusted. The effect of this combustion on the tunnel and train wall has been investigated. For this goal, two different mass flow rates of hydrogen were considered and results were compared together. Moreover, pressure contours have been shown to represent the overpressure phenomenon and it is resulted that in the area of hydrogen dispersion, there will be high pressure.

LOANS SETTLEMENT AT FEDERAL INTERNATIONAL FINANCE Ltd. (FIF) BANDAR LAMPUNG CITY

There are many ways to purchase a vehicle, including a credit system. However, various problems arise in its application regarding the settlement of bad loans caused by default debtors. This study aims to analyse the efforts made by Federal International Finance Ltd. (FIF) Bandar Lampung City in resolving motor vehicle bad loans due to default debtors. This study uses empirical normative legal research methods and qualitative descriptive methods. The data is obtained from direct observations and interviews, then linked to legal regulations concerning the default problem. The results indicate that Federal International Finance Ltd. has an ideal solution to resolve bad Loans through litigation and non-litigation. Efforts to settle bad loans through non-litigation could be made by giving a subpoena to the debtor. Furthermore, the creditor could take litigation by filing a civil lawsuit against the debtor for default according to Article 1243 of the Civil Code.

Sustainable performance analysis and ranking of organizations through fuzzy multi-criteria group decision making - A case study

In this paper, a decision support methodology for multiple attributes group decision making problem is developed. The proposed methodologies are based on Data Envelopment Analysis (DEA), Grey Relation analysis (GRA) and hybrid GRA-DEA methods. These methods are implemented for evaluation and ranking of organizations in sustainable perspective. In the proposed methods, the payoff values of alternatives are expressed in linguistic terms, given by the decision makers. Then, these linguistic terms are described by triangular fuzzy numbers. Charnes model of DEA is formulated in fuzzy environment to determine efficiencies of DMUs. Following the GRA method’s algorithm, a relative closeness coefficient is defined to determine the ranking order of all alternatives by calculating the distances to the fuzzy positive-ideal solution (FPIS), as well as to the fuzzy negative-ideal solution (FNIS). Also, performance evaluation of these companies is made through hybrid GRA-DEA in fuzzy environment. The weights of the criteria are determined objectively during evaluation of these companies in the proposed GRA and DEA-GRA methods. Comparison of proposed approaches is made and final ranking of the organizations is sustainable perspective is arrived. The proposed methodologies are illustrated with a case study of five steel manufacturing companies in India.

Decision Support System for Employee Performance Using AHP Method

The system supports the company's performance appraisal using the AHP (Case Study: PT. Andhy Putra) method, one of which is to find, select, assess and determine the best employees every year to match the abilities and assessment criteria applied so far. PT. Andhy Putra while assessing employee performance, especially in CME and OSP, still experiences shortcomings and weaknesses in determining qualified employees. This employee performance system has problems in assessing the performance appraisal data that is less accurate, which is carried out on a paper-based basis and requires less efficient time and large costs. For that, we need a decision support system in helping PT. Andhy Putra to conduct a performance appraisal every year. The method used in this employee assessment is AHP (Analytical Hierarchy Process), which is often also known as the weighting method. The process hierarchy analytical method is one of the methods used to find weight values ​​based on existing criteria and helps facilitate the ranking of alternatives based on the distance between the positive ideal solution and the negative ideal solution. There are 5 (five) criteria as a tool to assess employee performance, namely commitment to the company, desire for achievement, cooperation, leadership and discipline accompanied by the results of the implementation of this process hierarchy method in the form of ranking the alternatives used. This decision support system is built using the PHP programming language and MySQL database

Urban Stormwater Resilience Assessment Method Based on Cloud Model and TOPSIS

To scientifically and quantitatively evaluate the degree of urban storm resilience and improve the level of urban stormwater resilience, based on the resilience theory, starting from the three attributes of resilience (resistance, recovery and adaptability), this paper establishes the framework of urban resilience evaluation indicator system under the background of stormwater disaster. Firstly, the weight of the indicator system is analyzed by the Delphi method and cloud model, and then the urban stormwater recilience evaluation model is constructed by using the cloud model and approximate ideal solution ranking method. Through the fuzzy description, the corresponding quantitative value is given to the qualitative indicator, so that the stormwater resilience of the city can be measured by accurate values. Finally, the feasibility of the model is verified by case analysis. The results show that the urban stormwater resilience evaluation theory and method based on cloud model and approximate ideal solution ranking method have important guiding significance to improve the level of urban stormwater resilience.

Adaptive replication strategy based on popular content in cloud computing

The cloud is an infrastructure that provides decentralized on-demand services. It allows consumers to pay only for the services they use. The consumer is the important entity in the cloud. The violation of the SLA contract between the consumer and the provider often leads to consequences because the service provider has to pay penalties. Data replication is emerging as an ideal solution to meet the new challenges of the cloud. This paper proposes a new replication strategy based on the popularity of data. This strategy adaptively selects the files to be replicated to improve the overall availability of data in the system, minimize query response time, and achieve the required quality of service. In addition, it dynamically determines the number of replicas to add and the best locations to store them. Experimental results show the effectiveness of the proposed strategy.