Search results

Complexity is the main challenge for present and future manufacturers. Assembly complexity heavily affects a product’s final quality in the fully automated assembly system. This paper aims to propose a new method to assess the complexity of modern automated assembly system at the assembly design stage with respect to the characteristics of both manufacturing system and each single component to be mounted. Aiming at validating the predictive model, a regression model is additionally presented to estimate the statistic relationship between the real assembly defect rate and predicted complexity of the fully automated assembly system.

The research herein extends the S. N. Samy and H. A. ElMaraghy’s model and seeks to redefine the predictive model using fuzzy evaluation against a fully automated assembly process at the assembly design stages. As the evaluation based on the deterministic scale with accurate crisp number can hardly reflect the uncertainty of the judgement, fuzzy linguistic variables are used to measure the interaction among influence factors. A dependency matrix is proposed to estimate the assembly complexity with respect to the interactions between mechanic design, electric design and process factors and main functions of assembly system. Furthermore, a complexity attributes matrix of single part is presented, to map the relationship between all individual parts to be mounted and three major factors mentioned in the dependency matrix.

The new proposed model presents a formal quantification to predict assembly complexity. It clarifies that how the attributes of assembly system and product components complicate the assembly process and in turn influence the manufacturing performance. A center bolt valve in the camshaft of continue variable valve timing is used to demonstrate the application of the developed methodology in this study.

This paper presents a developed method, which can be used to improve the design solution of assembly concept and optimize the process flow with the least complexity.

To find the system with minimum investment and best quality performance that is capable of producing all of the product variants, assessing the complexity of designing assembly system at the early concept stage is an essential step, which helps and instructs a designer to create a product- and system-oriented assembly solution with the least complexity. The purpose of this paper is to propose a quantifying measurement of complexity in the design of a modular automated assembly system.

The configurable assembly system is becoming a trend, which enables companies to quickly respond to changes caused by different product variants but without a large investment. One of the enabling factors is the availability of modular solutions of assembly modules that can be configured according to different technical requirements. This paper develops a methodology using fuzzy evaluation to calculate the design complexity in the design phase for a modular automatic assembly system. Fuzzy linguistic variables are used to measure the interaction among the influence factors, to deal with the uncertainty of the judgement. The proposed method investigates three matrices to present how the function-based assembly modules, design complexity factors, part attributes and product components, which are regarded as the main influence factors, complicate the construction of a modular assembly system. The design complexity is derived and quantified based on these assessments.

The proposed approach presents a formal quantification to evaluate the design complexity with regard to a modular assembly system from beginning, which can be identified and used as criteria to indicate the quality of performance and investment cost in advance. A mathematical model based on the fuzzy logic is established to provide both theoretical and practical guidance for the paper. To validate the predictive model, the statistic relationships between the assessed system design complexity, real assembly defect rate and investment cost are estimated based on regression analysis. The application of the presented methodology is demonstrated with regard to a traditional rear drive unit in the automotive industry.

This paper presents a developed method, which addresses the measures of complexity found in the design of a modular assembly system. It would help to run the design process with better resource allocation and cost estimation in a quantitative approach.

This paper aims to establish an organizational learning system model based on both western and Chinese management thoughts.

The approach is a conceptual model which is based on research within the field.

The model consists of nine interrelated organizational learning sub‐systems including “discovering”, “innovating”, “selecting”, “executing”, “transferring”, “reflecting”, “acquiring knowledge from environment”, “contributing knowledge to environment”, and “building organizational memory” ones. The evidences in some famous Chinese traditional cultural classics (including Great Learning, Doctrine of the Mean, The Analects of Confucius, Book of Change, Tao‐Te‐Ching, The Art of War and Chuan‐Xi‐Lu) that support the rationale of the model are described and analyzed.

Several propositions are developed and it is hoped that the model is applicable in both eastern and western business environments.

This study aims to investigate the factors driving viewers' purchase intention in live-streaming by incorporating stimuli–organism–response (S–O–R) framework and extroversion–introversion personality perspectives.

Data collected from 228 users on live-streaming platforms in Taiwan were used to test the proposed model. The partial least squares method was used to test the measurement and the structural models.

Product attractiveness and trust in streamer significantly impacts purchase intention. The results also reveal that interactivity, breadth of information and uniqueness of information significantly impact product attractiveness, whereas social presence, breadth of information and uniqueness of information positively affect trust in streamer. Furthermore, streamer attractiveness has a greater effect on the purchase intention of extroverts.

This study investigates how the features of media, message and streamer impact purchase intention through their reactions to live-streaming. This research is also one of the earliest studies to examine the moderating role of extroversion–introversion personality on purchase intention and its antecedents in live-streaming commerce.

This study aims to investigate tourists’ impressions of the smart destinations model from the socio-technical systems and the technology–organization–environment (TOE) perspectives. Specifically, it aims to explore how information source credibility and cloud infrastructure influence tourists’ use of intelligent technology.

This measurement development is based on prior literature; after being evaluated for face and content validity, the authors used random sampling to collect data and conducted a field survey of tourists through Taoyuan Airport and using the airport MRT between December 2022 and March 2023. After confirming that tourists knew the destination information and had experience using travel-related mobile applications to plan their itinerary, the authors further invited tourists to participate in the survey, and 512 valid questionnaires were analyzed by the structural equation modeling approach.

The finding pointed out that source credibility and intelligent technology were innovative technologies that benefitted tourists, as were mobile travel planning apps, which created a relational context based on interests and activities from the socio-technical and TOE perspectives.

Technological innovation is closely related to the development of smart cities; tourists who used travel itineraries successfully understood travel-related actions and significantly had more positive affective images of the city.

This research aimed to examine the role of cloud infrastructure capabilities of tourism small and medium-sized enterprises (SMEs) in the tourism supply chain, increasing the online consumption value of tourists.

This study uses stratified random sampling. A value model was formulated, and the study distributed 2,000 surveys; 412 valid responses were received and analyzed using the structural equation modeling approach.

The cloud-based architecture provides tourism SMEs a competitive advantage in the dynamic tourism market and the ability to develop next-generation system capabilities while providing tourism SMEs with a new application foundation to adapt to the ever-changing tourism market.

For tourism SEMs, the cloud allows adjusting strategies and procedures for tourism supply chain management; this agility enables tourism SMEs to anticipate changes in the travel market and respond to changing consumer demands in the tourism industry.

This paper aims to investigate how the perception of physical coldness (vs warmth) influences consumers to make charitable donations.

Three experiments were conducted involving charitable donation scenarios.

Studies demonstrate that cold (vs warm) temperature cues result in greater intentions to donate to charities. Specifically, cold (vs warmth) cues activate the need for social connection which, in turn, motivate consumers to donate more money to charities. Furthermore, this effect holds even when the actual temperature instead of temperature cues is changed, and participants’ actual donation behavior instead of donation intentions is measured, thereby, strengthening the findings of this paper.

Boundary conditions associated with the effect of temperature cues need empirical investigation. Future research needs to investigate if the effect holds with variability of coldness. Future research also needs to determine whether the documented effect occur across various pro-social contexts.

The results suggest that non-profit organizations incorporate “cold” cues into advertisements (people feeling cold or cold landscapes) to increase monetary donations and that these organizations should focus on targeting donors during wintertime (vs summer time) to get more donations.

This is the first research to demonstrate the effects of temperature cues on charitable donations. The added value of this paper is the use of physical temperature change to highlight the phenomenon, and the link between cold (vs warm) temperature cue and the need of social connection.

This study examines how customer-linking capabilities, the flexibility of back-end management systems, strategic agility and the perceived absorptive capacity of e-commerce influence the organizational performance of online sellers.

A performance model based on the adaptive structuration theory was employed to test the hypotheses using structural equation modeling (SEM) on a dataset of 325 samples with acceptable responses.

The results reveal that the customer-linking capability and flexibility of back-end management systems, strategic agility and assimilation of e-commerce activity significantly influence organizational performance in a virtual environment.

The agility of online sellers is becoming increasingly important, and from the perspective of adaptive structuration theory, back-end management systems have been built to manage buyer orders for online sellers.

The purpose of this paper is to develop a theoretical model to investigate the determinants of continuance intention toward social networking sites (SNSs) by integrating the perspectives of the uses and gratifications theory, perceived interactivity and network externalities.

Data collected from 255 Facebook users in Taiwan were used to test the proposed model. The partial least squares method was used to test the measurement model and the structural model.

The findings reveal that emotional gratifications and social gratifications are the key predictors of users’ continuance intention toward SNSs. Further, the results indicate that perceived network size, perceived complementarity, machine interactivity and person interactivity influence information gratifications significantly, while perceived complementarity, machine interactivity and person interactivity exert positive effects on emotional gratifications. Finally, the results show that machine interactivity and person interactivity impact social gratifications positively, whereas perceived network size and perceived complementarity affect machine interactivity and person interactivity significantly.

This study is one of the earliest research inquiries to examine the effects of various types of gratifications on continuance intention. It is also one of the earliest studies to identify the antecedents of gratifications from social factors and technological attributes simultaneously.