Jian Wang, Yi Tan, Jingzhi Zhang and Yajuan Han
Quality function deployment (QFD) has been widely applied in new product development, but existing research on QFD has some limitations. Primarily, QFD lacks the capability to…
Abstract
Purpose
Quality function deployment (QFD) has been widely applied in new product development, but existing research on QFD has some limitations. Primarily, QFD lacks the capability to provide feedback on the satisfaction degree of customer requirements (CRs) according to the actual values of engineering characteristics (ECs). In addition, QFD does not quantitatively consider the interrelationships among ECs. Reverse QFD (R-QFD) was introduced to implement the feedback process. On this basis, this paper quantitatively considers the interrelationships among ECs in the R-QFD model and extends these relationships to encompass combinations of multiple ECs, aiming to improve the inference accuracy of the model.
Design/methodology/approach
A nonlinear regression model was established between CRs and ECs, aiming to infer the satisfaction degree of CRs based on the implementation status of ECs. This model considers the interdependencies among ECs and extends the consideration of pairwise EC correlations from every two to every fifteen. Lingo Software is utilized to seek solutions for this program. To facilitate the implementation of the program, a directive to simplify the solution has been proposed.
Findings
The experimental results indicate that the interrelationships among ECs significantly affect the inference accuracy of the R-QFD model, thereby verifying the necessity of considering higher-order interrelationships among ECs within the R-QFD framework. Based on the results from data experiments, this paper also proposes research recommendations pertaining to ECs hierarchy for varying quantities of ECs.
Originality/value
The outcomes of this study have further refined the R-QFD model, addressing its limitations of ignoring the interrelationships among ECs. This transformation elevates the R-QFD model from a relatively simple linear model to a nonlinear model formed through modeling, thereby enhancing its accuracy and applicability. In practical terms, this study provides case support for the application of the R-QFD model in manufacturing industry.
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Keywords
Yuling Chen, Jingzhi Shao, Charles Weizheng Chen and Fang Wan
Small talk, often regarded as a superficial interaction unrelated to work, is a pervasive and inescapable aspect of daily life and professional settings. In China, where the…
Abstract
Purpose
Small talk, often regarded as a superficial interaction unrelated to work, is a pervasive and inescapable aspect of daily life and professional settings. In China, where the notion of guanxi – the cultivation of strategic relationships – is deeply valued, workplace small talk (WST) is a strategic tool used by employees to strengthen their interpersonal networks. This study aims to investigate the positive impact of WST on task performance within the Chinese workplace and explores the mechanisms underpinning this relationship.
Design/methodology/approach
This study adopted a time-lagged research design to test its hypotheses using data from 516 employees across various Chinese firms.
Findings
This study revealed that WST exerts both direct and indirect positive effects on task performance. It boosts task performance indirectly via two mediators: relational energy and positive affect. This study also delineated a chain mediation model wherein WST sequentially elevates task performance by first enhancing relational energy and then fostering positive affect.
Originality/value
Counter to the prevailing focus on the negative repercussions of WST, this study sheds light on its beneficial outcomes, proposing novel pathways connecting WST to task performance. These insights contribute to both academic discourse and the development of practical management strategies.