Purpose
The purpose of this paper is to explore the direct effect of classical predictors of an individual’s behaviour, namely, attitude, subjective norms (SN) and perceived behavioural control (PBC) ...on the intention to deal with Islamic banks. The study extended the Theory of Planned Behaviour (TPB) by introducing the customers’ religiosity paradigm as a moderator between the classical predictors of the theory and the intention to deal with Islamic banks.
Design/methodology/approach
By applying the Theory of Planned Behaviour (TPB) framework, data were collected from conventional banks to investigate the potential Islamic bank customers’ intention. Using self-administered questionnaires, the data were collected from conventional banks in Muscat. A total of 1,000 questionnaires were distributed; however, only 638 were found usable. The structural equation modelling (SEM) was used to test the hypothesis and analyse the prediction values of the model in the TPB framework. It is also used to analyse the moderation effect of religiosity on the relation between the predictors and intention.
Findings
The results of the SEM analysis indicated that attitude, SN and PBC significantly predicted the potential customers’ intention to deal with Islamic banks in Oman. The results of the moderation effect shown that religiosity was a poor moderator of the relation between the attitude and intention as well as the PBC and intention, though, the result shown that religiosity is a partial moderator of the relation between the SN and intention.
Research limitations/implications
Due to the current study method, the result findings should be generalised with caution. Future studies may introduce other variables to examine the moderation effect between the relation of the predictor and intention of the TPB framework. It also signifies the moderation effect of religiosity on the relationship between the attitude, SN and PBC and intention of the potential customs in the TPB framework. This is considered a theoretical enrichment to the behaviour studies and TPB literature.
Practical implications
The current study assists the Islamic bank practitioners and regulators to broaden the horizon in considering the practical outcomes from the academic research. The result from this study does not only prove that the TPB seems to be acceptable in explaining the intention and behaviour in the field of Islamic banking but also support the robustness of the ability of TPB in predicting the behaviour and intention in a different research context (Islamic banking and finance).
Originality/value
This study is an attempt to introduce religiosity as a moderator in the TPB framework with SEM analysis and to explore the moderation effect between the predictors and intention to deal with Islamic banks among Omani’s Islamic Bank Customers. This study endeavours to fill a gap of these moderation effects and how the customers’ religiosity influence customer’s preferences towards Islamic Bank.
•A joint facility location and inventory model is developed.•Partial-disruption risk is considered.•A modified particle swarm optimization is proposed to solve the model.•The impact of the customer's ...decision to accept or reject backorder has analyzed.•The use of substitute products as a risk management strategy has analyzed.
This paper studies a joint facility location and inventory model from the viewpoint of partial-disruption risk—i.e., when manufacturing facilities meet the demands of third-party distribution centers with a portion of their capacity, free from any disruptions—while considering substitute products as a disruption risk mitigation strategy. We considered these third-party distribution centers as the customers of the manufacturing facilities. We used a multinomial logit model to rank-order the facilities according to customers’ preferences. Then, a non-linear integer programming model was developed which attempted to assign a sequence of facilities to each customer based on their preferences while at the same time, minimizing the total supply-chain cost. We also considered customers’ decisions for backorders while developing the model. Due to the NP-hard nature of the problem, we developed a particle swarm optimization-based metaheuristic algorithm to solve the model. The efficiency of the modified particle swarm optimization (MPSO) was illustrated through computational tests and systematic comparison with the exact method, a hybrid meta-heuristic algorithm including tabu search (TS) and variable neighborhood search (VNS) from the literature, and its modified form (Modified TS-VNS). A numerical example was used to show the applicability of the model. Finally, we gained useful insight into the role of substitute products and customers’ decisions for backorders through scenario-based analysis. We found that the total supply chain cost could increase in disruption scenarios when customers were more likely to refuse backorder offers. However, the cost-saving from producing a substitute for key products could be significant.
The maximal covering location problem (MCLP) is a well-known combinatorial optimization problem with several applications in emergency and military services as well as in public services. ...Traditionally, MCLP is a single objective problem where the objective is to maximize the sum of the demands of customers which are served by a fixed number of open facilities. In this article, a multi-objective MCLP is proposed where each customer has a preference for each facility. The multi-objective MCLP with customers’ preferences (MOMCLPCP) deals with the opening of a fixed number of facilities from a given set of potential facility locations and then customers are assigned to these opened facilities such that both (i) the sum of the demands of customers and (ii) the sum of the preferences of the customers covered by these opened facilities are maximized. A Pareto-based multi-objective harmony search algorithm (MOHSA), which utilizes a harmony refinement strategy for faster convergence, is proposed to solve MOMCLPCP. The proposed MOHSA is terminated based on the stabilization of the density of non-dominated solutions. For experimental purposes, 82 new test instances of MOMCLPCP are generated from the existing single objective MCLP benchmark data sets. The performance of the proposed MOHSA is compared with the well-known non-dominated sorting genetic algorithm II (NSGA-II), and it has been observed that the proposed MOHSA always outperforms NSGA-II in terms of computation time. Moreover, statistical tests show that the objective values obtained from both algorithms are comparable.
•A new multi-objective maximal covering location problem is proposed.•Customers’ preferences for different potential facility locations are considered.•A Pareto optimality-based multi-objective harmony search algorithm is proposed.•NSGA-II and CPLEX optimizer are used for performance comparisons.
Product competitiveness is highly influenced by its related design specifications. Information retrieval of customers preferences for the specification determination is essential to product design ...and development. Big sales data is an emerging resource for mining customers preferences on product specifications. In this work, information entropy is used for customers preferences information quantification on product specifications firstly. Then, a method of information mining for customers preferences estimation is developed by using big sales data. On this basis, a density-based clustering analysis is carried out on customers preferences as a decision support tool for the determination and selection of product design specifications. A case study related to electric bicycle specifications determination using big sales data is reported to illustrate and validate the proposed method.
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•A variant of the p-median in which customer preferences are taken into account, named the p-median bilevel problem with order, is studied.•A comparison among two single-level ...reformulations herein proposed and an adaptation of an existing reformulation for the SPLPO is made.•A hybrid heuristic algorithm based on Scatter Search and GRASP that obtains high-quality solutions in reasonable time is proposed.•A fair comparison with regards to other heuristic procedures (Scatter search, GRASP and Genetic algorithm) is performed.•A large set of instances in which the proposed heuristic obtains the best results when solving large-size instances is tested.
A variant of the p-median problem is considered and presented in this paper. This variant is based on the assumption that customers are free to choose the located facility that will serve them. The latter decision is made by considering the customers preferences towards the facilities. To study this problem, a mathematical bilevel programming formulation is proposed. Given the difficulty in solving such bilevel programs, two reformulations are used for solving the problem. The first reformulation adds constraints and variables to the mathematical model, while the second one adds only constraints. Yet, both reformulations avoid the need to solve an optimization problem parameterized by the upper level variables to find the value of the lower level variables. The results of numerical experiments show that the required time for both reformulations is significant increased as the size of the instance increases. Moreover, the reformulations are unable to solve the large-size instances. This led us to develop a hybrid heuristic algorithm based on scatter search, which obtains high-quality solutions for all tested instances in less time than is required by the abovementioned reformulations. Furthermore, the proposed heuristic was able to solve larger-size instances obtaining the optimal or currently best known solution. The registered results from the computational experimentation show that the proposed algorithm performs steadily. A comparison against a scatter search with random construction, a scatter search with greedy construction, a GRASP and a genetic algorithm shows that the proposed hybrid heuristic outperforms the other algorithms.
Purpose: The purpose of this research is to have better insight regarding come out with a conceptual framework in studying the brand preference in Islamic Muslimah fashion industry ...development.Muslimah fashion industries are areas that have attracted attention, especially after the recent wave among brand endorser such an artist increases their level of awareness towards the religious and affected way of their attire. This study highlights a significant shift in consumers' behavior regarding brand preferences and investigates the motives behind such moves.
Methodology: This paper explores the three independent variables and gathers findings from qualitative data through the literature on factors influencing customers' preferences for Muslimah fashion.Future branding empirical research would include these elements as items in building up the survey instrument.
Results: The results show that uniqueness, price, and celebrity endorser are among the determining factors that influence customers' preferences in making decisions.
Implications: Understanding customers' preferences on Muslimah fashion are crucial for a company that operates in fashion industries due to such a highly competitive industry and rapid change on taste and preference. Having a good understanding of the real motives behind customers' preferences on Muslimah fashion will help the business organization to understand customers better.These results will eventually be used for developing a conceptual framework to be used for future empirical research.
The uncapacitated facility location problem (UFLP) is a well-known combinatorial optimization problem having single-objective function. The objective of UFLP is to find a subset of facilities from a ...given set of potential facility locations such that the sum of the opening costs of the opened facilities and the service cost to serve all the customers is minimized. In traditional UFLP, customers are served by their nearest facilities. In this article, we have proposed a multi-objective UFLP where each customer has a preference for each facility. Hence, the objective of the multi-objective UFLP with customers’ preferences (MOUFLPCP) is to open a subset of facilities to serve all the customers such that the sum of the opening cost and service cost is minimized and the sum of the preferences is maximized. In this article, the elitist non-dominated sorting genetic algorithm II (NSGA-II), a popular Pareto-based GA, is employed to solve this problem. Moreover, a weighted sum genetic algorithm (WSGA)-based approach is proposed to solve MOUFLPCP where conflicting two objectives of the problem are aggregated to a single quality measure. For experimental purposes, new test instances of MOUFLPCP are created from the existing UFLP benchmark instances and the experimental results obtained using NSGA-II and WSGA-based approaches are demonstrated and compared for these newly created test instances.
This paper centres to the presentation of analyzed potential relations between the determinants of purchasing decisions regarding insurance products and socio-demographic variables, i.e. age, gender, ...place of residence, income, occupational status, and number of people in the household. The authors also examined whether making financial decisions in a household determines purchasing decisions concerning insurance products. The main hypothesis is: from the perspective of an elderly customer, inherent features of an analyzed insurance product are more vital than aspects regarding the sales process. The analysis was conducted using the ordered logit model, where factors determining purchases of insurance products were used as dependent variables.
Concurrent engineering has been generally accepted as an important approach to reduce time to market. For years, the focus of concurrency has been design and manufacturing. With customers’ inputs ...becoming more crucial for product development, incorporating customers’ preferences into the design process has become significant in the continuing quest for reducing time to market. Because customers’ preferences involve intricate interdependency on factors such as product attributes, deterministic methods often fall short of representing and manipulating their probabilistic nature. This paper presents a probabilistic model that could continuously incorporate and adapt customers’ preferences into the concurrent engineering methodology.
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