Search results

This study aims to examine the effect of Muslim consumers’ religiosity on their brand verdict regarding clothing brands, through the mediating role of decision-making style, brand status and brand attitude.

Structural equation modeling was used to analyze the data collected from 200 clothing buyers in Mashhad, one of Iran’s religious cities.

The results indicate that intrapersonal religiosity, compared to interpersonal religiosity, has a more significant effect on Muslim consumers’ decision-making styles, and different decision-making styles of Muslim consumers affect their brand verdict through brand status and brand attitude.

The research sample consists solely of respondents from the Islamic religion. Therefore, the impact of religiosity might differ among individuals from other religions, such as Christianity and Judaism.

This study’s findings are crucial for clothing brands, both national and international, that cater to the Muslim customers’ market. They need to consider the degree of religiosity when segmenting and targeting their market. This study shows that clothing brand marketers can best influence the brand verdict of Muslim consumers by targeting those with a brand-loyal decision-making style, focusing on their religious beliefs.

To achieve success in Iran’s Muslim market, marketers must consider their consumers’ religious beliefs and tailor their marketing plans accordingly. This study aims to investigate the impact of religiosity on consumer behavior toward brands in Iran’s Muslim market.

Based on the job demand and resource (JD–R) model, this study identifies the factors influencing fatigue among seafarers in Malaysia.

A total of 250 responses were gathered via an online survey applying a purposive sampling method. The derived data were analysed using partial least squares-structural equation modelling (PLS-SEM) via SmartPLS 4.

Job demand positively influences sleep problems and occupational stress, while job resources positively impact job autonomy. The research analysis also confirms the positive effect of sleep problems and occupational stress on fatigue. Furthermore, the study reveals the negative effect of job autonomy on fatigue. In-depth analysis confirms the mediation and sequential mediation effects as the determinants of fatigue among seafarers in Malaysia.

Besides enriching the literature on fatigue, the findings provide practical insights to maritime agencies to develop an effective policy to reduce fatigue among seafarers.

The study develops a new model for seafarers’ fatigue via the JD–R model by introducing work pressure, sleep problems, occupational stress and autonomy as sequential mediators.

The aim of this paper is to classify suppliers into some clusters based on sustainability factors. However, there might be some unqualified suppliers and we should identify and remove those suppliers before clustering.

First, using fuzzy screening system, the authors identify and remove the unqualified suppliers. Then, the authors run their proposed clustering method. This paper proposes a data envelopment analysis (DEA) algorithm to cluster suppliers.

This paper presents a two-aspect DEA-based algorithm for clustering suppliers into clusters. The first aspect applied DEA to consider efficient frontiers and the second aspect applied DEA to consider inefficient frontiers. The authors examine their proposed clustering approach by a numerical example. The results confirmed that their method can cluster DMUs into clusters.

The main contributions of this paper are as follows: This paper develops a new clustering algorithm based on DEA models. This paper presents a new DEA model in inefficiency aspect. For the first time, the authors’ proposed algorithm uses fuzzy screening system and DEA to select suppliers. Our proposed method clusters suppliers of MPASR based on sustainability factors.