This paper is about creating a hybrid QFD-based approach in which the best supplier is selected considering changing customer needs. In most previous studies employing a QFD approach, the possibility of changing customer needs is ignored. On the other hand, supplier selection is a challenging problem that could have been addressed by such a QFD. This paper attempts to create a hybrid QFD-based approach in which the internal relations between the elements are considered. It connects the new QFD to suppliers’ qualifications to create a hybrid supplier selection process. The best suppliers are selected based on the priorities of customer needs for each level of the product improvement plan. When a product is to be developed, the proposed methodology seems to create an efficient solution for supplier selection problem with respect to quality factors.

The purpose of this study is to examine the determinants of behavioral intentions to use of mobile health (m-Health) applications in Jordan through examining the mediating role of perceived trust and its influence on the behavioral intention to use such applications. A conceptual model was developed based on the extant literature. A questionnaire survey was administered to a convenient sample of 318. Data was analyzed using smart PLS 3. The findings suggest that patients’ behavioral intentions to use m-Health applications are positively affected by perceived ease of use, perceived security, social influence and perceived trust of these applications. Perceived Trust was also found to mediate the relationship between these factors and the behavioral intention. Discussion, conclusions, implications, research limitations and areas for future research are also provided.

In this study an integrated model is proposed for the location inventory routing problem under uncertainty. This problem involves determining the location of distribution centers (DCs) in a three echelon supply chain. The DCs receive orders from the customer and according to a continuous review inventory replenishment policy place orders to the supplier. The products are directly shipped from the supplier to the DCs. The vehicles start from the DCs to fulfill the demands of the customers. Determining the routing of the vehicles is one of the decisions involved in this problem. The demands of customers are stochastically distributed and the capacity of DCs are limited. If one of the DCs undergo a disruption and is unable to fulfill the demands of the customers, shortage may occur. Moreover in the proposed model the shortage is considered as partial backlogging. This means that if shortage occurs, some of the orders result in lost sales and other orders are fulfilled in the next period. In order to optimally solve the proposed model a nonlinear integer programming (INLP) model is developed. However, since the problem is NP-hard, the mathematical formulation cannot be efficiently solved for large sized instances of the problem. Therefore an outer approximation method is developed to solve the problem more efficiently. The computational results show the efficiency of the proposed method.

This study aims to provide an attempt by raising a framework for assessing the digital technology perspective in the application of Financial Technology by consumers, especially in the era of the Covid19 pandemic in 2020 in Indonesia. Digital technology in Fintech in collaboration with online transportation is utilized by quite a few big firms in Indonesia to meet the needs of consumers during strict, large-scale restrictions but not lockdown. This paper mainly acknowledged the problem related to digitizing solid digital technology which prioritizes technology 4.0. Digital technology applications, especially among the millennial generation regarding the accessibility, pace and value of financial services are increasingly in demand. This research spent 5.5 months with millennial respondents who are accustomed to using everyday technology applications in Jakarta, Depok and Tangerang and surrounding areas. The method of analyzing data in a quantitative way to find findings is complemented by discussion. The findings prove that; All variables have positive strong effect on driving the choice of digital FinTech technology in ordering food and others to survive during the pandemic of COVID-19. The existence of digital-based technology applications related to the internet, big data, smart mobile phones, safe and comfortable technology power has motivated consumers to use them. In conclusion, there are several new business opportunities open to newcomers in the digital financial sector and other accessories using information systems and information ecosystems.

The new method to chart the Hodges-Lehmann estimator control chart is proposed in this study. The evaluation of the three nonparametric control charts - the Sign test (ST), Mann-Whitney (MW), and the Hodges-Lehmann estimator (HL), for the known process distribution using normal and Weibull data represent the symmetric and asymmetric shapes of the process based on the original method through the 10000 run lengths simulation. The result illustrates that the average run length performance of the ST and MW correspond to their respective test statistics but for HL’s performance, the result indicates that the average run length is much greater than that derived from Wilcoxon signed rank statistics. The Hodges-Lehmann estimator control chart by the new approach for the known process distribution will be the alternative method for the process that needs to robust outliers’ properties from this statistics. In addition, the simulation demonstrates that the performances of the Sign test (ST) from mean and median processes are varied in the skewed distribution, and moreover, the Sign test (ST) from the median process represents more accurate performance. Meanwhile, for the control groups, MW generated within control limits or without restriction shows slightly different performance. The performance of dual scheme for the above-mentioned variable parameters control charts also produce the weighted average values that effect from the tight control scheme to the regular control scheme.

This study aims to explain the role of relational capability and informational capability in mediating the effect of social media adoption on business performance. The population of this study is the owners of the fashion sector SMEs in Bali. The sample size used was 114 businesses with a purposive sampling approach. The analytical technique used is Path Analysis using the SEM-PLS approach. The results show that the adoption of social media has a positive and significant effect on business performance. Social media adoption has a positive and significant effect on relational capability and social media adoption also has a positive and significant effect on informational capability. Furthermore, relational capability has a positive and significant effect on business performance and informational capability has a positive and significant effect on business performance. Relational capability and informational capability can significantly mediate the effect of social media adoption on business performance. Therefore, it is important for SME owners in the fashion sector in Bali to intensify the adoption of social media to build relational and informational capabilities in order to increase business performance.

Agricultural tractor selection is vital for farms, farmers or other agricultural companies in terms
of success and competitiveness in the global market. This selection may be assumed as a
MCDM (Multi Criteria Decision Making) problem involving qualitative and quantitative
factors that must be simultaneously integrated into the selection process. At the same time there
are many agricultural tractor alternatives in the market when purchasing an agricultural tractor.
This paper deals with the agricultural tractor selection problem using TOPSIS method. This
problem is also solved with two other MCDM methods; COPRAS (COmplex PRoportional
ASsessment) and EVAMIX (EVAluation of MIXed Data) to rank the tractors alternatives.
Lastly Borda and Copeland methods are used to aggregate all three ranking results.

This paper derives a production inventory model over infinite planning horizon with flexible but unreliable manufacturing process and the stochastic repair time. Demand is stock dependent and during the period of sale it depends on reduction on selling price. Production rate is a function of demand and reliability of the production equipment is assumed to be exponentially decreasing function of time. Repair time is estimated using uniform probability density function. The objective of the study is to determine the optimal policy for production system, which maximizes the total profit subject to some constraints under consideration. The results are discussed with a numerical example to illustrate the theory.

The purpose of this study was to determine the effect of value barriers, risk barriers, image barriers, cost barriers and usage barriers on the use of mobile banking in millennial generation customers. This research used a quantitative approach and the sampling technique used is purposive sampling which conducts research on a group of subjects with certain characteristics or is considered closely related to previously known population characteristics. This research was conducted by distributing 140 online questionnaires to mobile banking users and there were 110 questionnaires that were reversed and processed. Sampling methods use snowball sampling. The results indicate that there was a positive but not significant effect between risk barriers and mobile banking adoption intentions. However, there was a negative influence between image barriers and mobile banking adoption intentions. Moreover, there was a positive influence between perceived cost barriers and mobile banking adoption intentions, there was a positive influence between the barriers to use and mobile banking adoption the intention to adopt. Finally, there was a significant influence between value barriers and mobile banking adoption intentions.

Machining of hardened work materials with appropriate levels of process parameters is still a burning issue in manufacturing sectors and challenging. It is because of pressing demand of surface quality which adversely affected by evolution of tool wear. Therefore the present investigation is undertaken to make a decision on parametric optimization of multi-responses such as flank wear and surface roughness during machining hardened AISI 52100 steel (55±1) steel using mixed ceramic insert under dry environment through grey relational analysis combined with Taguchi approach. Also predicted mathematical models of 1st and 2nd order have been developed for responses and checked for its accuracy. Second order mathematical model presented higher R2 value and represents best fit of the model and adequate compared to first order model. Model indicates good correlations between the experimental and predicted results. The proposed grey-based Taguchi methodology has been proved to be efficient for solving multi-attribute decision making problem as a case study in hard machining environment.