Search results

The purpose of this paper is to develop a scale to find the relationship between consumer doubt, skepticism, familiarity, information seeking, value for money and aesthetic design with customers’ purchase intention.

This study focussed on students of Malaysian university of multimedia in Melaka campus and used questionnaires to obtain the relevant data. Convenience random sampling method is used whereby 200 questionnaires were distributed among the target population and exactly 200 completed answers were collected.

The survey results show that aesthetic design and information seeking of a product has a positive significant relationship with customers’ purchase intention. Respondents reported a consideration on these two factors and it is revealed that the scale used in this study is reliable and valid kind of measurement to assess customers’ purchase intention.

To minimize the innovating failure among launched new innovative products, managers and decision makers should focus on variables used in this study. By focussing on aesthetic design and information seeking they can overcome some of the problems cause failure.

This research focus on customers’ purchase intention to buy a Malaysian-made innovative new product and their lack of confidence and trust if the product satisfy their needs. The scale in this study show that this research is valid and it gives new perception toward purchase intention and innovation.

The construction industry contributes to economic development by providing physical equipment and infrastructures. However, it also generates some undesirable outputs such as waste and environmental pollution, especially in developing countries. Due to the importance of the green supply chain management (GSCM) philosophy, for solving these problems, the current study aims to evaluate the drivers of GSCM adoption in the construction industry of Iran.

This research uses a descriptive and practical methodology. The participated experts in the study include senior managers of the construction department in Rasht municipality who had relevant academic education and suitable experiences in urban and industrial construction. The experts took part in both qualitative and quantitative phases of the research, namely verification of the drivers extracted from literature and ranking them in ascending order. In the quantitative phase, Step-Wise Weight Assessment Ratio Analysis (SWARA) as a new multi-criterion decision-making (MCDM) method is used to evaluate the drivers of GSCM adoption using MATLAB software.

The results show that environmental management systems, green product design and innovational capability with weights of 0.347, 0.218 and 0.143 are the most significant sub-drivers, respectively. The less important factor is an investment in environmental technology.

This study evaluated the motivational factors of GSCM in the construction industry. The findings help governments, companies and green supply chain (GSC) managers to improve their knowledge about GSCM and make the best decisions to decrease environmental pollution.

The purpose of this study is to propose a hybrid reliability-centered maintenance (RCM) approach for mining transportation machines of a limestone complex, a real case in Esfahan, Iran.

Criteria for selecting critical machines were collected within literature and selected by decision-makers (DCs), and critical machines have been identified using the preference ranking organization method for enrichment of evaluations (PROMETHEE). Also, multi-criteria decision-making (MCDM) methods were used in addition to failure mode, effects and criticality analysis (FMECA) for selecting and prioritizing high-risk failures as well as optimizing the RCM performance. More specifically, the criteria of severity, detectability and frequency of occurrence were selected for risk assessment based on the previous studies, and were weighted using the analytic hierarchy process (AHP) method. Also, the technique for order of preference by similarity to ideal solution (TOPSIS) has been applied to prioritize failures' risk. Finally, the critical failures were inserted in the RCM decision-making worksheet and the required actions were determined for them.

According to the obtained values from PROMEHTEE method, the machine with code 739-7 was selected as the first priority and the most critical equipment. Further, based on results of TOPSIS method, the failure mode of “Lubrication hole clogging in crankpin bearing due poor quality oil,” “Deformation of main bearing due to overwork” and “The piston ring hotness due to unusual increase in the temperature of cylinder” have the highest risks among failure modes, respectively.

RCM has been deployed in various studies. However, in the current study, a hybrid MCDM-FMECA has been proposed to cope with high-risk failures. Besides, transportation machineries are one of the most critical equipment in the mining industry. Due to noticeable costs of this equipment, effective and continuous usage of this fleet requires the implementation of proper maintenance strategy. To the best of our knowledge, there is no research which has used RCM for transportation systems in the mining sector, and therefore, the innovation of this research is employment of the proposed hybrid approach for transportation machineries in the mining industry.

A set of routers that are connected over communication channels can from network-on-chip (NoC). High performance, scalability, modularity and the ability to parallel the structure of the communications are some of its advantages. Because of the growing number of cores of NoC, their arrangement has got more valuable. The mapping action is done based on assigning different functional units to different nodes on the NoC, and the way it is done contains a significant effect on implementation and network power utilization. The NoC mapping issue is one of the NP-hard problems. Therefore, for achieving optimal or near-optimal answers, meta-heuristic algorithms are the perfect choices. The purpose of this paper is to design a novel procedure for mapping process cores for reducing communication delays and cost parameters. A multi-objective particle swarm optimization algorithm standing on crowding distance (MOPSO-CD) has been used for this purpose.

In the proposed approach, in which the two-dimensional mesh topology has been used as base construction, the mapping operation is divided into two stages as follows: allocating the tasks to suitable cores of intellectual property; and plotting the map of these cores in a specific tile on the platform of NoC.

The proposed method has dramatically improved the related problems and limitations of meta-heuristic algorithms. This algorithm performs better than the particle swarm optimization (PSO) and genetic algorithm in convergence to the Pareto, producing a proficiently divided collection of solving ways and the computational time. The results of the simulation also show that the delay parameter of the proposed method is 1.1 per cent better than the genetic algorithm and 0.5 per cent better than the PSO algorithm. Also, in the communication cost parameter, the proposed method has 2.7 per cent better action than a genetic algorithm and 0.16 per cent better action than the PSO algorithm.

As yet, the MOPSO-CD algorithm has not been used for solving the task mapping issue in the NoC.