Pengaruh Kualitas Pelayanan Terhadap Kepuasan Pelanggan Dan Konsekuensinya Pada Loyalitas (Studi Pada Obyek Wisata Di Kabupaten Malang)

Studi ini meneliti kepuasan wisatawan yang mengunjungi obyek wisata yang ada di Kabupaten Malang dengan menggunakan konsep dasar Swedish Customer Satisfaction Barometer (SCSB). Tujuan penelitian untuk menganalisis pengaruh langsung kualitas layanan (service quality) terhadap kepuasan wisatawan domestik (customer satisfaction), menganalisis pengaruh langsung harapan konsumen (customer expectation) terhadap kepuasan wisatawan domestik (customer satisfaction), dan menganalisis pengaruh langsung kepuasan konsumen (customer satisfaction) terhadap loyalitas konsumen (customer loyalty) wisatawan domestik. Sampel penelitian adalah wisatawan domestik yang berkunjung ke objek wisata (Pantai Sendang Biru, Pantai Ngliyep dan Pantai Bale Kambang), yaitu sebanyak 150 responden. Teknik analisis data yang digunakan adalah Structural Equation Modelling (SEM) dengan menggunakan bantuan program AMOS. Hasil penelitian menunjukkan bahwa ada pengaruh langsung antara kualitas layanan dan kepuasan pelanggan, tidak ada pengaruh yang signifikan anatara harapan dengan kepuasan pelanggan, ada pengaruh langsung antara kepuasan pelanggan dengan loyalitas konsumen. Variabel kualitas layanan yaitu reliability dan emphaty memiliki pengaruh yang paling besar terhadap kepuasan pelanggan sedangkan responsiveness, assurance, dan tangible memilki pengaruh yang cukup signifikan

Fast computation and characterization of forced response surfaces via spectral submanifolds and parameter continuation

For mechanical systems subject to periodic excitation, forced response curves (FRCs) depict the relationship between the amplitude of the periodic response and the forcing frequency. For nonlinear systems, this functional relationship is different for different forcing amplitudes. Forced response surfaces (FRSs), which relate the response amplitude to both forcing frequency and forcing amplitude, are then required in such settings. Yet, FRSs have been rarely computed in the literature due to the higher numerical effort they require. Here, we use spectral submanifolds (SSMs) to construct reduced-order models (ROMs) for high-dimensional mechanical systems and then use multidimensional manifold continuation of fixed points of the SSM-based ROMs to efficiently extract the FRSs. Ridges and trenches in an FRS characterize the main features of the forced response. We show how to extract these ridges and trenches directly without computing the FRS via reduced optimization problems on the ROMs. We demonstrate the effectiveness and efficiency of the proposed approach by calculating the FRSs and their ridges and trenches for a plate with a 1:1 internal resonance and for a shallow shell with a 1:2 internal resonance

A Novel Clustering Model Based on Set Pair Analysis for the Energy Consumption Forecast in China

The energy consumption forecast is important for the decision-making of national economic and energy policies. But it is a complex and uncertainty system problem affected by the outer environment and various uncertainty factors. Herein, a novel clustering model based on set pair analysis (SPA) was introduced to analyze and predict energy consumption. The annual dynamic relative indicator (DRI) of historical energy consumption was adopted to conduct a cluster analysis with Fisher’s optimal partition method. Combined with indicator weights, group centroids of DRIs for influence factors were transferred into aggregating connection numbers in order to interpret uncertainty by identity-discrepancy-contrary (IDC) analysis. Moreover, a forecasting model based on similarity to group centroid was discussed to forecast energy consumption of a certain year on the basis of measured values of influence factors. Finally, a case study predicting China’s future energy consumption as well as comparison with the grey method was conducted to confirm the reliability and validity of the model. The results indicate that the method presented here is more feasible and easier to use and can interpret certainty and uncertainty of development speed of energy consumption and influence factors as a whole

dsRNA Virus Model Molecule and the Mechanism of PRRs and its Research Progress in Female Reproductive Tract Infections

Female animal genital tract opening on the body surface, prone to bacterial, viral, parasitic, and other pathogenic microorganism infections, leading to genital tract infectious diseases, such as endometritis, cervicitis, vaginitis, etc. Severe infection can lead to infertility, abortion, and even fetal death. Double-stranded RNA (dsRNA) is an important model molecule, which is widely present in the genome of viruses and generated in the process of virus replication. In mammals, dsRNA is considered to be an innate immune response signal for viral infection, which binds to the corresponding pattern-recognition receptors (PRRs) In vivo and then exerts biological functions. This review summarizes the signal transduction pathway induced by the binding of dsRNA model molecules to PRRs, research status of female genital tract infections and research progress of dsRNA in simulating viral infection in the female genital tract

Risk Evaluation of Debris Flow Hazard Based on Asymmetric Connection Cloud Model

Risk assessment of debris flow is a complex problem involving various uncertainty factors. Herein, a novel asymmetric cloud model coupled with connection number was described here to take into account the fuzziness and conversion situation of classification boundary and interval nature of evaluation indicators for risk assessment of debris flow hazard. In the model, according to the classification standard, the interval lengths of each indicator were first specified to determine the digital characteristic of connection cloud at different levels. Then the asymmetric connection clouds in finite intervals were simulated to analyze the certainty degree of measured indicator to each evaluation standard. Next, the integrated certainty degree to each grade was calculated with corresponding indicator weight, and the risk grade of debris flow was determined by the maximum integrated certainty degree. Finally, a case study and comparison with other methods were conducted to confirm the reliability and validity of the proposed model. The result shows that this model overcomes the defect of the conventional cloud model and also converts the infinite interval of indicators distribution into finite interval, which makes the evaluation result more reasonable