Due to the advancement of technology and rapidly changing environment of the market, the life cycle of high‐tech products is becoming shorter. The enterprise must…
Due to the advancement of technology and rapidly changing environment of the market, the life cycle of high‐tech products is becoming shorter. The enterprise must constantly innovate and select correct development strategy of new product in order to respond to customers’ demands for upgrading operational performance of industry. Development of new product is the critical activity for enterprise’s survival and growth. This research focuses on the effects of Taiwan high‐tech companies’ introduction of innovative activity and development strategy of new product on development performance of new product for analysis and exploration. The result findings reveal that: (1) High execution degree of innovative activity has positive effect on the implementation of development strategy of new product; (2) The companies with better implementation of development strategy of new product reveal better development performance; (3) The companies with higher degree of execution of innovative activity and better execution of development strategy of new product reveal better development performance of new product.
Decision makers in the service industry must effectively cope with queuing problems, service capacity optimization, service efficiency and service quality problems. This…
Decision makers in the service industry must effectively cope with queuing problems, service capacity optimization, service efficiency and service quality problems. This study proposes a computer simulation‐enabled MCDM framework that integrates computer simulation analysis, Taguchi method, expert opinion and multiple criteria decision making (MCDM) to assist decision makers in coping with decision problems. In this framework, Taguchi method is adopted to reduce the time required for the simulation experiment. Computer simulation analysis is adopted to obtain useful information for rapid decision‐making without interrupting actual production. MCDM is used to select the optimal alternative. The illustrative result is extremely promising.
In recent years, speedy development of Taiwan’s hotel industry intensifies market competition, customers’ demands on hotel services quality also increase with the increase…
In recent years, speedy development of Taiwan’s hotel industry intensifies market competition, customers’ demands on hotel services quality also increase with the increase of their consumption consciousness, and their demands on hotel types diversify, therefore hotel industry should concern on their unique management services quality brought by their different hotel types. The current designed service system or service transmission process may fail to meet customers’ demands owing to emphasizing degree gap in service quality. What is worse, it is difficult for hotel industry to actualize complete customer segregation and to provide customized services, therefore comprehensive understanding of customers’ demands on the service quality of different types hotels would contribute to operating management improvement of Taiwan hotel industry. This paper divides Taiwan hotels into three types: international tourism commercial type, holiday type and motel, the general hotels. It studies the emphasize degree gap in service quality between the industry and the customers. Data analysis shows that service quality gap (perceived gap) of hotels of different types exists in several quality aspects; what’s more, the perceived gaps, service quality aspects, and its items of different types of hotel are also different. After an integrated analysis, this paper puts forward a general and customer‐oriented quality item suitable for hotel industry to shorten the perceived gap of service quality, so that the hotel industry could design a service system and service transfer system, which could meet most lodging customers’ demands in the context of pluralized customer sources.
Failure mode and effects analysis (FMEA) is a preventive technique in reliability management field. The successful implementation of FMEA technique can avoid or reduce the…
Failure mode and effects analysis (FMEA) is a preventive technique in reliability management field. The successful implementation of FMEA technique can avoid or reduce the probability of system failure and achieve good product quality. The FMEA technique had applied in vest scopes which include aerospace, automatic, electronic, mechanic and service industry. The marking process is one of the back ends testing process that is the final process in semiconductor process. The marking process failure can cause bad final product quality and return although is not a primary process. So, how to improve the quality of marking process is one of important production job for semiconductor testing factory. This research firstly implements FMEA technique in laser marking process improvement on semiconductor testing factory and finds out which subsystem has priority failure risk. Secondly, a CCD position solution for priority failure risk subsystem is provided and evaluated. According analysis result, FMEA and CCD position implementation solution for laser marking process improvement can increase yield rate and reduce production cost. Implementation method of this research can provide semiconductor testing factory for reference in laser marking process improvement.
The purpose of this paper is to propose a novel approach of fuzzy importance‐performance analysis (FIPA) to replace conventional importance‐performance analysis (IPA) for…
The purpose of this paper is to propose a novel approach of fuzzy importance‐performance analysis (FIPA) to replace conventional importance‐performance analysis (IPA) for determining critical service attributes those really need to improve for achieving superior customer satisfaction.
First, referring numerous studies, conventional IPA has some erroneous assumptions, the customer satisfaction of attribute performance has the characteristic of three‐factor theory and the novel approach which integrates natural logarithmic transformation and partial correlation analysis is feasible for acquiring the implicitly derived importance of attributes. Second, according the fact and nature of fuzziness in human perception, this study applies fuzzy set theory to revise conventional IPA. Finally, the FIPA is proposed and subsequently implemented in a Taiwanese hot spring hotel case study.
The implementation of FIPA shows the determined critical service attributes are almost completely different from those attributes acquired by conventional IPA. Hence, the application of conventional IPA may cause practitioners make incorrect decisions of improvement priorities for service attributes and direct unsuitable quality‐based marketing strategies.
The proposed FIPA which integrates fuzzy set theory, three‐factor theory, partial correlation analysis and natural logarithmic transformation avoids the erroneous assumptions of conventional IPA, considers the nature of fuzziness in human perception and includes the actual importance of service attributes. Therefore, the proposed FIPA can effectively assist business managers in determining critical service attributes to improve service quality or customer satisfaction and to achieve competitive advantage.
This investigation applied a hybrid method combining a trained artificial neural network (ANN) and the sequential quadratic programming (SQP) method to determine an…
This investigation applied a hybrid method combining a trained artificial neural network (ANN) and the sequential quadratic programming (SQP) method to determine an optimal parameter setting for a reflow soldering process of ball grid array packages in printed circuit boards.
Nine experiments based on an orthogonal array table with three‐controlled inputs and average shear forces of solder spheres as a quality target were utilized to train the ANN and then the SQP method was implemented to search for an optimal setting of parameters.
The ANN can be utilized successfully to predict the shear force under different reflow soldering conditions after being properly trained and the identified optimal parameter setting are capable of striking the balance between the average shear forces and the manufacturing cycle time.
The reflow time and the peak temperature were found to be the most significant factors for the reflow process via analysis of variance.
This study provided an algorithm integrating a black‐box modeling approach (i.e. the ANN predictive model) with the SQP method to resolve an optimization problem. This algorithm offered an effective and systematic way to identify an optimal setting of the reflow soldering process. Hence, the efficiency of designing the optimal parameters was greatly improved.