This study empirically investigates the mediating effect of brand satisfaction on the relationship between brand personality and brand loyalty among Malaysian customers toward local automobile brands (Proton and Perodua). Four hypotheses were developed to test hypothesizing relationships between brand personality and brand satisfaction on brand loyalty. The data were collected from consumers of automobile brands in north Malaysia peninsula from three states which were Kedah, Penanag, and Perlis. This study applies partial least squares to a sample of 458 customers to test hypothesized relationships. The findings indicate that brand personality and brand satisfaction appear to have a positive and significant relationship with brand loyalty. Moreover, brand satisfaction was found to be a mediator in the relationship between brand personality and brand loyalty. The results are compared with earlier findings and implications for further research are discussed.

This study aims to analyze the improvement of the operational performance of Indonesia’s Soekarno-Hatta Airport train through service quality which is mediated by train passenger loyalty and passenger satisfaction. The main problems in this study are the use of the same railway for long-distance train, airport train, and commuter Line train, the limited use of airport railway with four schedules, the headway which becomes 30 minutes since the number of travels becomes 82 trips, and the tariff being applied now is considered as burdening the passengers. The research method uses a quantitative analysis approach with the technique of Structural Equation Modeling-Lisrel. Data collection is done through observation and questionnaire distribution. The respondents are 306 passengers of trains heading for Soekarno-Hatta Airport. The benefit of this study for the domestic railway company is that by improving service quality, passenger loyalty and satisfaction, it will improve the operational performance of airport trains. The result of this research indicates the significant influence of service quality variable on passenger loyalty through passenger satisfaction, the significant influence of service quality variable on operational performance through passenger satisfaction and passenger loyalty as well as the significant influence of passenger satisfaction variable on operational performance through passenger loyalty.

This article presents a broad review of Hub location problem (HLP), and its applications. The goal of this article is to provide a review on the newest and most recent publications on Hub location and its application in real world practices since 2013. While, there are some articles which reviewed hub location problem literature but some models were not covered in those articles. In this paper, we try to include capacitated models. We survey advances in analysis and modeling of the hub location problem including its variants and solution algorithm of HLPs. We emphasize the most applicable areas for Marine Transpiration. We show that first, majority of the articles consider network domain, while there are some articles which execute HLP in discrete and continuous domain. Also, the capacitated case attracts more attention in recent years. Finally, the contribution of any type of HLP in the literature is shown schematically.

Weather forecasting is essential and demanding scientific task of meteorological services across the world. It is a complex procedure that includes many specific technological field of study. The prediction is intricate process in meteorology because all decisions are made within a facet of uncertainty associated with weather systems. This research finding introduces a novel rough fuzzy computing approach for a short term rainfall forecasts. The model consists of rough set based optimal weather parameter selection module and fuzzy rule based classification module. The proposed fuzzy decision support model is compared with benchmarked classification approaches. The fuzzy classification model used in fuzzy decision support system is trained and tested using the reduct sets generated using proposed maximum frequency weighted feature reduction technique. The optimal reduct set constituting the weather parameters; minimum temperature, relative humidity and solar radiation achieved better prediction accuracy than complete feature set and the reducts. Most of the classification models have shown better accuracy when trained using the selected subsets of the target input. Thorough evaluation of the proposed model has revealed that coupling fuzzy decision support system and rough based pre-processing techniques was a better approach than traditional techniques. The experimental results revealed the proposed rough fuzzy model as a better rainfall prediction approach for modeling short range rainfall forecast.

Social media empowers small and medium enterprises (SMEs) in engaging with their stakeholders economically and effectively. Social media use affects SMEs operation and knowledge sharing which creates innovation opportunities, speeds time to market, satisfies firm's customers, and improves business performance. Current research aims to explore the impact of social media use on the market entry agility, product innovativeness, reducing the market entry time for the SME and improving the firm performance. Cross-sectional survey-based data was collected from the jewelry crafting SMEs in Bali, Indonesia. The data was analyzed with the covariance-based statistical analysis technique with the SPSS based AMOS 23. The study results identify that social media use and market entry agility significantly impact firm performance. However, product innovativeness insignificantly influences firm performance. Furthermore, the market entry agility mediates for the firm performance so, SMEs need to leverage social media use, and market entry agility enables the dynamic capacity to enhance firm performance. Firms’ level innovativeness capability should be considered as a mediating role but should support another variable to leverage firm performance. The study limitation and future research options are reported at the end.

The aim of this study is to establish a framework for measuring and managing credit risk for fifteen leasing companies in Iran. An analysis on the influence of internal factors on credit performance will then be performed. This will enable a leasing industry to progress towards its goals and objectives in the most direct and effective way. Credit risk consists of probability of non-return. This may be in the form of bankruptcy or a decrease in financial and credit situation of the lessee. We can assume a correlated market and credit risk. The variables are extracted from the Central Bank of Kanoon Leasing Association in Iran. Numerical analysis reveals that lessee credit risk can have a substantial impact on a lease term structure.

Web services have become quite popular over the last few years as they allow easier development and integration of business applications. In this paper, we consider a web service pricing problem where two providers compete through dynamic pricing. Each provider offers access to a web service with different quality classes where users may buy their required web service through a reservation system. They would like to adjust the prices of their web services over a pre-specified time horizon to manage demand and to maximize profit. Users have the right with no obligation to cancel their services as long as they pay a penalty. We consider a dynamic setting where the web service classes share a capacity. We first develop a time continuous model for competitive pricing of a web service and then we provide some insights about the equilibrium condition of the problem using open-loop differential game and propose an algorithm to obtain the optimal pricing policy for providers. Moreover, we conduct numerical analyses to examine the impacts of some parameters on control and state variables.

Consumers today are individuals who fulfill life needs such as shopping using e-commerce. In its fulfillment, consumers can change in terms of purchasing decisions from one e-commerce to another e-commerce. This requires the company to always have a good strategy to compete in a healthy manner in terms of business. To learn about the importance of social media marketing activity, this study will find out how much influence the social media marketing activity received by e-commerce companies has on brand equity, customer relationships and repurchase intention. In addition, the study will learn how much influence brand equity and customer relationship have on an e-commerce company's repurchase intention. In this study, the survey is conducted by distributing questionnaires to respondents online where the research sample has several questions related to the habits and behavior of respondents. This research uses a sample of 210 people who are domiciled in Indonesia. In the research model, the study uses Structural Equation Modeling (SEM) analysis and the software used for this research is IBM SPSS AMOS. The results of the influence of social media marketing activities have the largest positive influence on customer relationships, brand equity is the main and biggest factor that positively and significantly affects repurchase intention in this research model. The accumulated experience and knowledge of consumers about a brand is a factor that can influence consumers to repurchase the same brand. Brand equity not only provides immediate benefits, but also long-term benefits by retaining consumers to continue to repurchase their products. A strong brand will make consumers always remember the brand. The study explains that customer relationships do not have any significant effect on repurchase intention. The main function of customer relationships at first and now is to try to reach their consumers more broadly, especially related to purchases, but this is not proven in repurchases, especially in this study. Customer relationships in the study did not have any significant effect on repurchase intention.

Today, Coronavirus is a pandemic that has spread worldwide and causes many problems, including socio economic problems in society. Therefore, e-marketing has an essential function in acquiring new customers, generating leads, and generating revenue for your business by reaching customers interested in your products and services. A digital platform such as web marketing is online marketing to prospective leads and high-value consumers. Thus, the present study examined the usage of e-marketing as a model for buying decisions moderated by perceived risk during the covid-19 pandemic in Aceh Province, Indonesia. This quantitative study involved 325 respondents and was collected through a survey by filling out the questionnaires. Also, e-marketing is measured by perceived usefulness, perceived ease of use as exogenous variables. Therefore, perceived risk is a mediating variable, and the consumer buying decision is an endogenous variable. The data were analyzed using Structural Equation Modelling – Analysis of Moments Structure (SEM-AMOS). The results showed that e-marketing (perceived usefulness and ease of use) positively and significantly affects consumer buying decisions. This study also applied the Sobel test and indicated that perceived risk mediates perceived usefulness and ease toward consumer buying decisions. In conclusion, this study has successfully examined the relationship between e-marketing via perceived usefulness and perceived ease of use. Also, it proves that perceived risk plays a mediating role (partial mediator) in the relationship of perceived usefulness and ease of use on consumer buying decisions. This tested model has become a formulation, especially in marketing science, where it turns out that during the covid-19 pandemic, the buying decision model in the marketplace is a function of the perceived usefulness and perceived ease of use of consumers towards the marketplace, as well as the perceived risk of the marketplace as a partial mediator. So that marketplace manufacturers can drive consumer buying decisions by consumers by creating a strengthening of perceived usefulness and perceived ease of use for consumers, thereby affecting consumers' perceived risk and impacting their buying decisions.

This paper presents a methodology for the design and integration of CONWIP in a make-to-order firm. The approach proposed was applied directly to the flexible job shop of a real manufacturing firm in order to assess the validity of the methodology. After the description of the whole plant layout, attention was focused on a section of the shop floor (21 workstations). The CONWIP system deals with multiple-product families and is characterized by path-type cards and a pull-from-the-bottleneck scheme. The cards release strategy and a customized dispatching rule were created to meet the firm’s specific needs. After the simulation model of the present state was built and validated, the future state to be implemented was created and simulated (i.e. the CONWIP system). The comparison between the two systems achieved excellent results, and showed that CONWIP is a very interesting tool for planning and controlling a complex flexible job shop.