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The purpose of this study is to apply hybrid cluster analysis in classifying PT Pelindo I customers based on the level of customer satisfaction with passenger services of PT Pelindo I.

Hybrid cluster analysis is a combination of hierarchical and non-hierarchical cluster analysis. This hybrid cluster analysis appears to optimize the advantages of hierarchical and non-hierarchical methods simultaneously to obtain optimal grouping. Hybrid cluster analysis itself has high flexibility because it can combine all hierarchical and non-hierarchical methods without any limits in the order of analysis used.

The results showed that 72% of PT Pelindo I customers felt PT Pelindo I service was special, while the remaining 28% felt PT Pelindo I service was good.

In total, 117 customers of PT Pelindo I were involved in a study using the non-probability sampling method.

This paper aims to propose a combined methodology to help decision makers in evaluating and selecting the most effective part feeding system.

As a first step of the methodology, a hierarchical clustering analysis is applied to design a kitting or hybrid feeding system. Second, activity-based costing methodology is applied to determine which system is better according to their costs. Besides, sensitivity analysis is implemented to observe the behavior of the system in case of the takt time changes.

Using kitting systems purely can lead to problems because of the big and expensive parts in the mixed-model assembly systems. Therefore, the hybrid feeding policy can provide better solutions for such systems.

A case study is conducted in a company and the most produced product of the company is considered to design the part feeding system. Results indicated that transportation cost has a large proportion on the total cost and the hybrid feeding policy may be a good solution to reduce this cost.

The paper includes implications for the design of hybrid feeding systems in lean-based assembly lines. The proposed methodology may be a practical tool for decision makers to design and decide on the part feeding policy.

Kitting design has not been studied yet to the best of the authors’ knowledge. Besides, there is no certain decision methodology indicating which system is better. In this study, different methods are combined as a new methodology with the purpose of industrial decision-making.

For those who plan research funds and assess the research performance from the funds, it is necessary to overcome the limitations of the conventional classification of evaluated papers published by the research funds. Besides, they need to promote the objective, fair clustering of papers, and analysis of research performance. Therefore, the purpose of this paper is to find the optimum clustering algorithm using the MATLAB tools by comparing the performances of and the hybrid particle swarm optimization algorithms using the particle swarm optimization (PSO) algorithm and the conventional K-means clustering method.

The clustering analysis experiment for each of the three fields of study – health and medicine, physics, and chemistry – used the following three algorithms: “K-means+Simulated annealing (SA)+Adjustment of parameters+PSO” (KASA-PSO clustering), “K-means+SA+PSO” clustering, “K-means+PSO” clustering.

The clustering analyses of all the three fields showed that KASA-PSO is the best method for the minimization of fitness value. Furthermore, this study administered the surveys intended for the “performance measurement of decision-making process” with 13 members of the research fund organization to compare the group clustering by the clustering analysis method of KASA-PSO algorithm and the group clustering by research funds. The results statistically demonstrated that the group clustering by the clustering analysis method of KASA-PSO algorithm was better than the group clustering by research funds.

This study examined the impact of bibliometric indicators on research impact of papers. The results showed that research period, the number of authors, and the number of participating researchers had positive effects on the impact factor (IF) of the papers; the IF that indicates the qualitative level of papers had a positive effect on the primary times cited; and the primary times cited had a positive effect on the secondary times cited. Furthermore, this study clearly showed the decision quality perceived by those who are working for the research fund organization.

There are still too few studies that assess the research project evaluation mechanisms and its effectiveness perceived by the research fund managers. To fill the research void like this, this study aims to propose PSO and successfully proves validity of the proposed approach.

To better understand the characteristics of Indonesian Muslims, this study uses cluster analysis to group upper-middle-class Muslims based on psychographic variables related to participation in cash waqf for productive purposes.

This study used mixed methods to build and analyse the segmentation of upper-middle-class Muslims towards cash waqf and propose scenarios for a cash waqf model based on the findings.

This study identified six clusters for upper-middle-class Muslims related to the participation in cash waqf for productive purposes. All clusters show heterogeneous values of all factors. Although relatively few Muslims perform cash waqf for productive purposes, the high scores for the economic rational, family and community factors indicate great potential for the development of various cash waqf models for investment purposes. The next challenge will lie in reviewing the “one-fits-all strategy” in the development of program, education and socialisation. Based on the findings, this study proposes three scenarios of cash waqf participation: as wakif only (waqf donor), investor only (capital provider) and hybrid participation (waqf donor and capital provider).

The limitation of this study is the location and object of the sample are only Muslims in Indonesia who are categorised as upper-middle class in terms of their monthly income. Based on this study’s findings, other Muslim-majority countries worldwide have the potential to develop a cash waqf model that is integrated with financial instruments and involves the role of Islamic banking and other Islamic commercial institutions in future research development. Researchers can also attempt to include a simulation or experiment method to construct and validate the proposed cash waqf model based on this study’s findings and to explore other factors that have not been addressed.

The findings of this study can contribute as a foundation for the development of a cash waqf model and business-marketing strategy to increase the participation of upper-middle-class Muslims.

The findings of this study will support the acceleration of cash waqf collection for investment initiatives, which in turn will have a broader social and economic impact nationally.

To the best of the authors’ knowledge, this study constitutes the first attempt to specifically investigate upper-middle-class Muslim segmentation toward cash waqf participation for productive purposes. This study’s knowledge is helpful for various stakeholders such as academia, the Islamic banking industry, regulators and the Muslim community about customer segmentation to Islamic banking products and services related to cash waqf.

In shopping, for selecting the appropriate garments, people have to try on multiple garments. This problem is due to lack of a sizing system based on updated anthropometric data and the classification system that introduces the appropriate size from the sizing chart to each person. To solve this problem, as a first study in the literature, a hybrid intelligent classification model as a size recommendation expert system is proposed. The paper aims to discuss these issues.

Three stages for developing a hybrid intelligent classification system based on data clustering and probabilistic neural network (PNN) are proposed. In the first stage, the clustering algorithm is used for specifying the sizing chart. In the second stage, the resulting sizing chart is used as a reference for developing a new intelligent classification system by using a PNN. At the last stage, the accuracy of the proposed model is evaluated by using the Iranian male's body type data set.

Experimental results show that the proposed model has a good accuracy and can be used as a size recommendation expert system to specify the right size for the customers. By using the proposed model and designing an interface for it, a decision support system was developed as a size recommendation expert system that was used by an apparel sales store. The results were time saving and more satisfying for the customers by selecting the appropriate apparel size for them.

In this paper, as a first study in literature, a hybrid intelligent model for developing a size recommendation expert system based on data clustering and a PNN to enable the salesperson to help the consumer in choosing the right size is proposed. In the first stage, the clustering algorithm is used for specifying the sizing chart. In the second stage, the resulting sizing chart is used as a reference to develop a new intelligent classification system by using a PNN. In the last stage, the accuracy of the proposed model is evaluated by using testing data. The proposed model achieved an 87.2 percent accuracy rate that is very promising.

The purpose of this paper is to examine the differences among the different subgroups of the youth market in the context of their financial interests and usage. The study examines what determined their choice of banks. It also looked at what factors influence their satisfaction, loyalty, and behavioral intentions with regard to their banking needs.

Using a multiple‐item survey instrument, 242 Austrian respondents were queried on what factors affect their choice of banks, their choice of financial services, usage patterns, satisfaction, loyalty, and behavioral intentions. Descriptive analysis, factor analysis and cluster analysis were employed in the study. Different tests such as chi‐square tests, discriminant analysis and ANOVA were used to validate the chosen cluster solution.

Differences were found among the four clusters in terms of their interest in financial services, their usage, and their likelihood of switching. In addition, determinants of satisfaction, loyalty, and behavioral intention were primarily affected by satisfaction with employees and services rendered. The results indicate that as young people reach certain milestones, their needs become more multifaceted. Consequently, banks should be aware of these changing needs.

This paper treats the youth market as a heterogeneous group rather than homogenous as many studies usually treat this age cohort. Moreover, given that many banks are trying to “grow” markets, the paper looks at how the determinant factors change from one stage to another. Financial institutions will benefit from the insight derived from this paper in crafting their marketing strategies. It indicates what seems to be important to each age group in increasing their satisfaction level.

This study aims to segment and profile young internet addicts in India and examine their state of well-being.

Young’s Internet Addiction Test was adapted to identify and profile cohorts among the internet addicts. Diener’s satisfaction with life scale was used to measure the well-being. Convenience sampling was used to conduct an online survey and obtain a representative sample of 320 urban internet users. A mixed-method approach was deployed and exploratory factor analysis followed by k-means cluster analysis and discriminant analysis were used to analyse the quantitative data.

Data analysis revealed the existence of three distinct clusters: non-addicts (135), potential internet addicts (n = 128) and addicts (n = 57). Smartphones and tablets were the primary devices for accessing the internet. Wi-Fi and data cards were used by all groups for internet browsing, messaging and visiting social networking sites. The usage hours were higher for the potential internet addicts and internet addicts. These groups also faced considerable internal conflict and dissonance in their inability to control their addictive behaviour and online cravings. The non-addicts were more satisfied with their life conditions and better adjusted than the other two groups.

The incidence of diverse internet addicted groups needs to be validated through a larger sample in other regions and geographies. There is also a dire need to study other vulnerable groups, such as internet-savvy adolescents.

The study found the existence of well-defined segments and identified unique areas of conflict for each group, which subsequently affected their sense of well-being.

The purpose of this study is two-fold: classifying non-Muslim halal fashion buyers by applying quantitative techniques and identifying the persuading determinants of the non-Muslim women’ halal fashion buying behaviour (HFBB).

By adapting items from prior studies, a structured questionnaire was developed and distributed face-to-face to various Muslim fashion stores in Malaysia. After a one-month effort, 221 responses were obtained from non-Muslim consumers by using convenience sampling. Next, a clustering analysis was used to classify them from a contrasting perspective. Finally, regression and Andrew F. Hayes’s process procedures were applied to examine the three independent variables’ effect and the moderating variables.

The results revealed the characteristic behaviour of the non-Muslim women explicitly, which is related to their halal fashion purchasing decision. Based on the ANOVA results, there were different motives for buying halal fashion by non-Muslim women. Additionally, it was found that the most crucial determinants for non-Muslim’s HFBB are “cultural adaptation”, albeit, there is no substantial proof of a significant moderating effect of age and income on the consumers.

These discoveries are advantageous for halal fashion retailers and provide an appealing domain for further investigations in the context of the global halal study.

This study provided an idea for an untapped segment on the halal fashion sellers’ segmentation and positioning strategy. The study’s results suggested specific managerial and practical recommendation that the sellers can use to attract non-Muslim consumers.

This study was amongst the uncommon investigations within the halal fashion context that will enlighten the managers’ selling strategy on the most neglected market segment. The results of this study provided an empirical understanding of how to sell halal fashion to non-Muslim consumers.

The purpose of this paper was to identify whether artificial intelligence (AI) products can possess human rights, how to define their rights and obligations and what ethical standards they should follow. In this study, the human rights ethical dilemma encountered in the application and development of AI technology has been focused on and analyzed in detail in the light of the existing research status of AI ethics.

In this study, first of all, the development and application of AI technology, as well as the concept and characteristics of human rights ethics, are introduced. Second, the human rights ethics of AI technology are introduced in detail, including the human rights endowment of AI machines, the fault liability of AI machines and the moral orientation of AI machines. Finally, the approaches to human rights ethics are proposed to ensure that AI technology serves human beings. Every link of its research, production and application should be strictly managed and supervised.

The results show that the research in this study can provide help for the related problems encountered in AI practice. Intelligent library integrates human rights protection organically so that readers or users can experience more intimate service in this system. It is a kind of library operation mode with more efficient and convenient characteristics, which is based on digital, networked and intelligent information science. It aims at using the greenest way and digital means to realize the reading and research of human rights protection literature in the literature analysis method.

Intelligent library is the future development mode of new libraries, which can realize broad interconnection and sharing. It is people-oriented and can make intelligent management and service and establish the importance of the principle of human rights protection and the specific idea of the principle. The development of science and technology brings not only convenience to people's social life but also questions to be thought. People should reduce its potential harm, so as to make AI technology continue to benefit humankind.