Chunxia Yu, Zhiqin Zou, Yifan Shao and Fengli Zhang
The purpose of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the artificial neural network (ANN)…
Abstract
Purpose
The purpose of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the artificial neural network (ANN), analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) methods.
Design/methodology/approach
In the proposed approach, the ANN model is used to classify decision maker’s risk attitude; the fuzzy AHP method is used to determine the relative weights of evaluation criteria; and the fuzzy TOPSIS method is used to evaluate ratings of suppliers. Finally, experiments are conducted to verify the feasibility and efficiency of the proposed integrated approach.
Findings
Experiments results show that the proposed integrated approach is effective and efficient to help decision makers to select suitable suppliers according to their risk attitudes.
Originality/value
The aim of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the ANN, AHP and TOPSIS methods. The decision maker’s risk attitude toward procurement transaction is originally considered in supplier selection process.
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Jaclyn Koopmann, Mo Wang, Yihao Liu and Yifan Song
In this chapter, we summarize and build on the current state of the customer mistreatment literature in an effort to further future research on this topic. First, we detail the…
Abstract
In this chapter, we summarize and build on the current state of the customer mistreatment literature in an effort to further future research on this topic. First, we detail the four primary conceptualizations of customer mistreatment. Second, we present a multilevel model of customer mistreatment, which distinguishes between the unfolding processes at the individual employee level and the service encounter level. In particular, we consider the antecedents and outcomes unique to each level of analysis as well as mediators and moderators. Finally, we discuss important methodological concerns and recommendations for future research.
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Shenghua Zhou, S. Thomas Ng, Sang Hoon Lee, Frank J. Xu and Yifan Yang
In the architecture, engineering and construction (AEC) industry, technology developers have difficulties in fully understanding user needs due to the high domain knowledge…
Abstract
Purpose
In the architecture, engineering and construction (AEC) industry, technology developers have difficulties in fully understanding user needs due to the high domain knowledge threshold and the lack of effective and efficient methods to minimise information asymmetry between technology developers and AEC users. The paper aims to discuss this issue.
Design/methodology/approach
A synthetic approach combining domain knowledge and text mining techniques is proposed to help capture user needs, which is demonstrated using building information modelling (BIM) apps as a case. The synthetic approach includes the: collection and cleansing of BIM apps’ attribute data and users’ comments; incorporation of domain knowledge into the collected comments; performance of a sentiment analysis to distinguish positive and negative comments; exploration of the relationships between user sentiments and BIM apps’ attributes to unveil user preferences; and establishment of a topic model to identify problems frequently raised by users.
Findings
The results show that those BIM app categories with high user interest but low sentiments or supplies, such as “reality capture”, “interoperability” and “structural simulation and analysis”, should deserve greater efforts and attention from developers. BIM apps with continual updates and of small size are more preferred by users. Problems related to the “support for new Revit”, “import & export” and “external linkage” are most frequently complained by users.
Originality/value
The main contributions of this work include: the innovative application of text mining techniques to identify user needs to drive BIM apps development; and the development of a synthetic approach to orchestrating domain knowledge, text mining techniques (i.e. sentiment analysis and topic modelling) and statistical methods in order to help extract user needs for promoting the success of emerging technologies in the AEC industry.
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Yifan Wang, Ryuichi Tani and Kenetsu Uchida
In the field of engineering, the fractional moments of random variables play a crucial role and are widely utilized. They are applied in various areas such as structural…
Abstract
Purpose
In the field of engineering, the fractional moments of random variables play a crucial role and are widely utilized. They are applied in various areas such as structural reliability assessment and analysis, studying the response characteristics of random vibration systems and optimizing signal processing and control systems. This study focuses on calculating the fractional moments of positive random variables encountered in engineering. This study focuses on calculating the fractional moments of positive random variables encountered in engineering.
Design/methodology/approach
By integrating Laplace transforms with fractional derivatives, both analytical and practical numerical solutions are derived. Furthermore, specific practical application methods are provided.
Findings
This approach allows for the stable and highly accurate calculation of fractional moments based on the integer moments of random variables. Data experiments included in this study demonstrate the effectiveness of this method in solving fractional moment calculations in engineering. Compared to traditional methods, the proposed method offers significant advantages in stability and accuracy, which can further advance research in the engineering field that employs fractional moments.
Originality/value
(1) Accuracy: Although the proposed method does involve some error, its error level is significantly lower than traditional methods, such as the Taylor expansion method. (2) Stability: The computational error of the proposed method is not only minimal but also remains stable within a narrow range as the fractional order varies. (3) Efficiency: Compared to the widely used Taylor expansion method, the proposed method requires only a minimal number of integer-order moments to achieve the desired results. Additionally, it avoids convergence issues during computation, greatly reducing computational resource requirements. (4) Simplicity: The application steps of the proposed method are very straightforward, offering significant advantages in practical applications.
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Rabia Shahid, Humera Shahid, Li Shijie, Faiq Mahmood and Ning Yifan
Using the Shanghai pilot free trade zone (SPFTZ) as the testing ground for further reform and opening up,the links between global value chain (GVC) and pilot free trade zone…
Abstract
Purpose
Using the Shanghai pilot free trade zone (SPFTZ) as the testing ground for further reform and opening up,the links between global value chain (GVC) and pilot free trade zone (PFTZ) programs are mutually reinforcing. GVC creates opportunities for companies to use PFTZ to reduce their costs and increase their competitiveness, while PFTZ can facilitate the movement of goods within GVC and promote the development of GVC by attracting foreign investment. Overall, in SPFTZ, the industrial structure is promoted due to trade and investment facilitation, innovation promotion, and comprehensive service platform inside SPFTZ.
Design/methodology/approach
This study examined industrial upgrading in GVC (IUGVC) using five indicators under three quantitative dimensions: product, process, and skill upgrading. Difference-in-Differences (DID) model is employed for the impact assessment of SPFTZ. Parallel trend analysis and Granger causality analysis are performed to check the reliability of DID outcome. Finally, robustness test using exogenous control variables are carried out.
Findings
A positive impact of SPFTZ is found on IUGVC, which is due to promoting effect of SPFTZ on foreign direct investment and technological innovation. Based on the study's findings, policy recommendations are given, such as providing business support to enterprises operating inside a PFTZ.
Originality/value
From a GVC perspective, the impact of theSPFTZ establishment on IUGVC cannot be ignored, and is so far missing in the literature.
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Guoliang Li, Yanran Fang, Yifan Song, Jingqiu Chen and Mo Wang
Given migrant workers’ critical role in the Chinese economy, the increasing number of migrant workers who leave their organizations and return to their hometown has caused severe…
Abstract
Purpose
Given migrant workers’ critical role in the Chinese economy, the increasing number of migrant workers who leave their organizations and return to their hometown has caused severe socioeconomic issues in China. The purpose of this paper is to contribute to migrant worker literature by revealing the micro-mechanism underlying migrant workers’ return-to-hometown intention and turnover.
Design/methodology/approach
Data were collected from a convenience sample from seven Chinese companies that employed migrant workers (n=147). The authors used path analysis to test the hypotheses.
Findings
Migrant workers’ family encouragement of returning to hometown was positively related to their return-to-hometown intention, which subsequently predicted their turnover decision in six months. Further, migrant workers’ perceived career sacrifice associated with returning to hometown weakened the effect of family encouragement to return.
Practical implications
For organizations that need to retain migrant workers, the findings indicate that it is particularly important to take migrant workers’ family needs and their career-related concerns into account. For migrant workers, the study highlights the importance of assessing gains and losses in the process of making turnover-related decisions.
Originality/value
This study contributes to migrant worker literature by investigating psychological processes underlying migrant workers return-to-hometown intention and the subsequent turnover from a micro perspective.
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Xianglu Hua, Lingyu Hu, Reham Eltantawy, Liangqing Zhang, Bin Wang, Yifan Tian and Justin Zuopeng Zhang
Achieving sustainability and sustainable performance has emerged as a critical area of focus for both academic research and practice. However, this pursuit faces challenges…
Abstract
Purpose
Achieving sustainability and sustainable performance has emerged as a critical area of focus for both academic research and practice. However, this pursuit faces challenges, particularly concerning the inadequacy of supply chain information. To address this issue, our study employs the organizational information processing theory to explore how adopting blockchain technology enables firms to learn from and collaborate with their supply chain partners, ultimately facilitating their sustainable performance even in the presence of organizational inertia.
Design/methodology/approach
Underpinned by the organizational information processing theory and drawing data from 220 manufacturing firms in China, we use structural equation modeling to test our conceptual model.
Findings
Our results demonstrate that blockchain technology adoption can significantly enhance sustainable performance. Furthermore, supply chain learning acts as a mediator between blockchain technology adoption and sustainable performance, while organizational inertia plays a negative moderating role between blockchain technology adoption and supply chain learning.
Originality/value
These findings extend the existing literature on blockchain technology adoption and supply chain management, offering novel insights into the pivotal role of blockchain in fostering supply chain learning and achieving sustainable performance. Our study provides valuable practical implications for managers seeking to leverage blockchain technology to enhance sustainability and facilitate organizational learning.
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Rabail Tariq, Yifan Wang and Khawaja Fawad Latif
Through the lens of resource-based view (RBV), knowledge-based view (KBV) and DCV, this paper aims to investigate the relationship of entrepreneurial leadership (EL) on the…
Abstract
Purpose
Through the lens of resource-based view (RBV), knowledge-based view (KBV) and DCV, this paper aims to investigate the relationship of entrepreneurial leadership (EL) on the project success (PS) and further examines the mediating effect of knowledge infrastructure capability (KIC), knowledge-based dynamic capability (KBDC) and Big data analytic capability (BDAC).
Design/methodology/approach
The data were collected from 467 employees working on project in software companies. The data were evaluated using SMART-PLS, a structural equation modeling (SEM) tool.
Findings
The study revealed a significant impact of EL on the PS, the study also found the significant mediation role of KIC, KBDC and BDAC on the EL and PS relationship.
Originality/value
The research gives valuable insight into the effective role of EL as a contemporary leadership style in project-based firms. Also, this research is one of the first to examine knowledge-oriented dynamic capabilities (DC) as a knowledge fulcrum in project execution. These DC have been empirically proven to facilitate EL in achieving PS and support the firm in competing in an uncertain environment.
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Sixing Chen, Jun Kang, Suchi Liu and Yifan Sun
This paper aims to build on the latest advances in cognitive computing techniques to systematically illustrate how unstructured data from users can offer significant value for…
Abstract
Purpose
This paper aims to build on the latest advances in cognitive computing techniques to systematically illustrate how unstructured data from users can offer significant value for co-innovation.
Design/methodology/approach
The paper adopts a general overview approach to understand how unstructured data from users can be analyzed with cognitive computing techniques for innovation. The paper links the computerized techniques with marketing innovation problems with an integrated framework using dynamic capabilities and complexity theory.
Findings
The paper identifies a suite of methodologies for facilitating company co-innovation via engaging with customers and external data with cognitive computing technologies. It helps to expand marketing researchers and practitioners’ understanding of using unstructured data.
Research limitations/implications
This paper provides a conceptual framework that divides co-innovation process into three stages, ideas generation, ideas integration and ideas evaluation, and maps cognitive computing methodologies and technologies to each stage. This paper makes the theoretical contributions by developing propositions from both customer and firm perspectives.
Practical implications
This paper can be used for companies to engage consumers and external data for co-innovation activities by strategically select appropriate cognitive computing techniques to analyze unstructured data for better insights.
Originality/value
Given the lack of systematic discussion regarding what is possible from using cognitive computing to analyze unstructured data for co-innovation. This paper makes first attempt to summarize how unstructured data can be analyzed with cognitive computing techniques. This paper also integrates complexity theory to the framework from a novel perspective.
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Dongmei Zhao, Yifan Xia, Haiwen Ge, Qizhao Lin, Jianfeng Zou and Gaofeng Wang
Ignition process is a critical issue in combustion systems. It is particularly important for reliability and safety prospects of aero-engine. This paper aims to numerically…
Abstract
Purpose
Ignition process is a critical issue in combustion systems. It is particularly important for reliability and safety prospects of aero-engine. This paper aims to numerically investigate the burner-to-burner propagation during ignition process in a full annular multiple-injector combustor and then validate it by comparing with experimental results.
Design/methodology/approach
The annular multiple-injector experimental setup features 16 swirling injectors and two quartz tubes providing optical accesses to high-speed imaging of flames. A Reynolds averaged Navier–Stokes model, adaptive mesh refinement (AMR) and complete San Diego chemistry are used to predict the ignition process.
Findings
The ignition process shows an overall agreement with experiment. The integrated heat release rate of simulation and the integrated light intensity of experiment is also within reasonable agreement. The flow structure and flame propagation dynamics are carefully analyzed. It is found that the flame fronts propagate symmetrically at an early stage and asymmetrically near merging stage. The flame speed slows down before flame merging. Overall, the numerical results show that the present numerical model can reliably predict the flame propagation during the ignition process.
Originality/value
The dedicated AMR method together with detailed chemistry is used for predicting the unsteady ignition procedure in a laboratory-scale annular combustor for the first time. The validation shows satisfying agreements with the experimental investigations. Some details of flow structures are revealed to explain the characteristics of unsteady flame propagations.