Analysis of Factors Affecting Consumer Purchase Behavior: Study in Muslim communities who shop online through the Shopee Application

This study aims to determine and analyze what factors influence consumer buying behavior in the era of citizen 4.0 and the most dominant influences on consumer buying behavior in citizen 4.0. This research uses descriptive and explanatory survey methods. Sampling was carried out using the Accidental Sampling sample technique. The data analysis technique used is factor analysis. The findings of this study are factors such as availability and price factors, promotion factors, comfort factors, varieties and comparison factors, after-sales service factors, and connectivity factors that influence consumer purchasing behavior in the era of citizen 4.0. Besides that, variety and comparison factors are the most dominant factors affecting consumer buying behavior in the age of citizen 4.0, followed by availability and price factors, comfort factors, promotion factors, after-sales service factors, and connectivity factors.

A Districting Application with a Quality of Service Objective

E-commerce sales have led to a considerable increase in the demand for last-mile delivery companies, revealing several problems in their logistics processes. Among these problems, are not meeting delivery deadlines. For example, in Chile, the national consumer service (SERNAC) indicated that in 2018, late deliveries represented 23% of complaints in retail online sales and were the second most common reason for complaints. Some of the causes are incorrectly designed delivery zones because in many cases, these delivery zones do not account for the demographic growth of cities. The result is an imbalanced workload between different zones, which leads to some resources being idle while others fail to meet their workload in satisfactory conditions. The present work proposes a hybrid method for designing delivery zones with an objective based on improving the quality of express delivery services. The proposed method combines a preprocess based on the grouping of demand in areas according to the structure of the territory, a heuristic that generates multiple candidates for the distribution zones, and a mathematical model that combines the different distribution zones generated to obtain a final territorial design. To verify the applicability of the proposed method, a case study is considered based on the real situation of a Chilean courier company with low service fulfillment in its express deliveries. The results obtained from the computational experiments show the applicability of the method, highlighting the validity of the aggregation procedure and improvements in the results obtained using the hybrid method compared to the initial heuristic. The final solution improves the ability to meet the conditions associated with express deliveries, compared with the current situation, by 12 percentage points. The results also allow an indicative sample of the critical service factors of a company to be obtained, identifying the effects of possible changes in demand or service conditions.

Application of Rough Set Theory to Improve Outpatient Medical Service Quality in Public Hospitals Based on the Patient Perspective

Purpose: To analyze the key factors and decision-making behaviors affecting overall satisfaction based on perceptual data of outpatients.Methods: The official satisfaction questionnaire developed by the National Health Commission of the People's Republic of China was used. Rough set theory was used to identify the perception patterns between condition attributes (i.e., service factors) and a decision attribute (i.e., overall service level) and to express them in rule form (i.e., if-then).Results: The four minimal-coverage rules, with strength exceeding 10% in the good class, and six crucial condition attributes were obtained: “Ease of registration (C1),” “Respected by registered staff (C2),” “Registered staff's listening (C3),” “Respected by doctor (C9),” “Signpost (C12),” and “Privacy (C16).” In addition, the average hit rate for 5-fold cross-validation was 90.86%.Conclusions: A series of decision rules could help decision-makers easily understand outpatients' situations and propose more suitable programs for improving hospital service quality because these decision rules are based on actual outpatient experiences.

An Integrated Analysis of Value-Based Adoption Model and Information Systems Success Model for PropTech Service Platform

This study develops a sustainable PropTech service model. Specifically, it analyzes the consumer-oriented and service provider-oriented service elements to build a sustainable ecosystem. This study also conducts a preliminary examination to standardize an efficient service platform reflecting the consumer and service factors. Hence, the study analyzes the service factors of users and derives a reference for the quality-of-service design using the value-based adoption model and the information systems success model, respectively. By integrating these models, we develop a tool to analyze empirically the important elements influencing PropTech users. To this end, we conducted a questionnaire survey among 530 PropTech users from 24 August 2021 to 14 September 2021. The results show that the consumer’s intention to use services is influenced by service practicability in terms of consumer value. The intention to continue using a service is influenced by user satisfaction. The results also highlight the importance of considering all the quality factors when building a user-friendly service platform. These findings have implications in that they show the importance of a sustainable PropTech service platform in resolving information asymmetry, promoting transparent transactions, and enhancing productivity in the real estate industry.

Contextual and mental health service factors in mental disorder-based disability pensioning in Finland – a regional comparison

Background We investigated the regional differences in all mental disorder disability pensions (DP) between 2010 and 2015 in Finland, and separately in mood disorders and non-affective psychotic disorder DP. We also studied the contribution of several district-level contextual and mental health service factors to mental disorder DP. Methods Subjects were all those granted mental disorder DP for the first time between 2010 and 2015 in Finland (N = 36,879). Associations between the district-level contextual and mental health service factors and regional DP risks collected from the year 2015 were studied with negative binomial regression analysis in the Finnish hospital districts. The population number on the age (18 to 65 years), gender, occupational status and residential hospital district of the Finnish population from 2015 was used as exposure in the model. Results Significant differences in the regional mental disorder DP risks between and within hospital districts did not appear to follow the traditional Finnish health differences. A lower risk of DP was associated with contextual indicators of higher regional socioeconomic level. Furthermore, population density as a proxy for access to mental health services indicated a higher regional DP risk for lower density in all mental (IRR 1.10; 95% CI 1.06–1.14) and mood disorder (IRR 1.12; 95% CI 1.08–1.16) DP. Both the highest and the lowest regional numbers of all mental health outpatient visits were associated with a higher DP risk in all mental and mood disorder DP, whereas particularly low regional numbers of inpatient treatment periods and of patients were associated with a lower risk of DP. Conclusions In this comprehensive population-level study, we found evidence of significant regional variation in mental disorder DP and related district-level factors. This variation may at least partly relate to differences in regional mental health service systems and treatment practices. Adapting to the needs of the local population appears to be indicated for both regional mental health service systems and treatment practices to achieve optimal performance.

The Influence of Service Factors on Customer Satisfaction in Makeup Salons

This study attempted to investigate the influence of makeup service factors on customer satisfaction empirically to provide basic data that would help makeup salons enhance customer satisfaction and set a proper direction for services. The results found the following: Among makeup service factors, ‘quality of cosmetics,’ ‘makeup artists’ skills,’ and ‘makeup artists’ reputation and kindness’ revealed a positive correlation with customer satisfaction with statistical significance. Also, ‘makeup artists’ reputation and kindness’ and ‘makeup artists’ skills’ positively affected customer satisfaction with statistical significance. The results confirm that ‘makeup artists’ reputation and kindness’ and ‘makeup artists’ skills’ have the greatest influence on customer satisfaction. The study results found that customer satisfaction with makeup services could be enhanced by increases in ‘reasonable service charge,’ ‘makeup artists’ skills,’ and ‘makeup artists’ reputation and kindness,’ thereby increasing revisit rates and making a significant contribution making makeup salons more competitive.