Improving the Management and Operational Success of the Third Party Logistics Industry in Taiwan: Application of Fuzzy Quality Function Deployment

Liao, Mao-Sheng; Lin, Shin-Yi; Liang, Gin-Shuh; Chen, Chin-Yuan

doi:10.1520/jte20130217

Cited by 6 publications

(3 citation statements)

References 67 publications

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“…The management and operational success requirements of the 3PL industry include the professional capability of service personnel and the operational process optimization. The fuzzy quality function deployment (FQFD) approach can support the identification of these requirements for improving the management and operational success [17]. Artificial intelligence solutions, especially expert systems, are also used in the human resource management domain to support the adequate selection and appointment of jobs applicants and employees from the point of view job rotation, recruitment, training, evaluation and job classification.…”

Section: State Of the Art In Human Resource Researchmentioning

confidence: 99%

Markov-Chain Simulation-Based Analysis of Human Resource Structure: How Staff Deployment and Staffing Affect Sustainable Human Resource Strategy

2018

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Manufacturing and service processes are composed of several elements: Technical, financial, logistics, information and human resources. Staff deployment and staffing is an essential problem in the human resource management domain because the structure of employees would be continuously in an optimal relationship to the jobs to be performed. This paper proposes a conceptual model for the analysis of human resource deployment processes. After a systematic literature review, it was found that algorithms are important tools for the design and control of human resource problems since a wide range of models determines an optimization problem. According to that, the main focus of this research is the modelling and analysis of human resource deployment processes of manufacturing companies using Markov-chain mathematics, also taking into account the absorbing phenomena of employees’ promotion. The main contribution of this article includes the model framework of Markov-chain simulation of a human resource deployment problem; the mathematical description of different human resource deployment strategies with subdiagonal and superdiagonal promotion matrices; the computational results of the described model with different datasets and scenarios. In the case of a given human resource strategy, the Markovian human resource deployment process of a company was analyzed. The analyzed model was the HR deployment of assembly line operators in a multinational company, including six levels of promotion. The results of the scenario analysis show that promotion and recruitment rates have a great impact on the future employees’ structure.

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Section: State Of the Art In Human Resource Researchmentioning

confidence: 99%

Markov-Chain Simulation-Based Analysis of Human Resource Structure: How Staff Deployment and Staffing Affect Sustainable Human Resource Strategy

2018

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“…However, due to subjective judgments made by customers and experts, the traditional models are unable to sufficiently cater for the uncertainties, vagueness, ambiguities and impreciseness [ 33 , 34 ]. Therefore, the fuzzy QFD was developed to get the better results [ 35 , 36 , 37 , 38 ]. Therefore, this study mainly applies fuzzy QFD to realize the transformation from customer requirements to operational strategies in the case of uncertainties and vagueness.…”

Section: Literature Reviewmentioning

confidence: 99%

Research on Evaluating the Sustainable Operation of Rail Transit System Based on QFD and Fuzzy Clustering

Yan

Wang

2020

Entropy

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The purpose of this study is to evaluate the sustainable operation of rail transit system. In rail transit system, as the most important aspect of negative entropy flow, the effective strategy can offset the increasing entropy of the system and make it have the characteristics of dissipative structure, so as to realize the sustainable operation. At first, this study constructs the Pressure-State-Response(PSR) model to evaluate the sustainable operation of rail transit system. In this PSR model, “pressure” is viewed as customer requirements, which answers the reasons for such changes in rail transit system; “state” refers to the state and environment of system activities, which can be described as the challenges of coping with system pressure; “response” describes the system’s actions to address the challenges posed by customer needs, namely operational strategies. Moreover, then, 13 pressure indices, five state indices and 11 response indices are summarized. In addition, based on quality function deployment (QFD), with 13 pressure indices as input variables, five state indices as customer requirements (CRs) of QFD and 11 response indices as technical attributes (TAs) of QFD, this study proposed the three-phase evaluation method of the sustainable operation of rail transit system to obtain the operational strategy (that is, negative entropy flow): The first phase is to verify that 13 pressure indices can be clustered into five state indices by fuzzy clustering analysis; The second phase is to get the weights of five state indices by evidential reasoning; The third phase is to rate the importance of 11 response indices by integrating fuzzy weighted average and expected value operator. Finally, the proposed model and method of evaluation are applied to the empirical analysis of Shanghai rail transit system. Finally, we come to the conclusion that Shanghai rail transit system should take priority from the following five aspects: “advancement of design standards”, “reliability of subway facilities”, “completeness of operational rules”, “standardization of management operation” and “rationality of passenger flow control”.

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“…As the conventional QFD method is not able to adequately interpret the ambiguity of thinking and expressing the preferences of decision-makers, one of the solutions is to integrate the fuzzy logic with the QFD method in order to increase the accuracy and objectivity. In recent years, the conventional or fuzzy QFD method is successfully applied to solve the problems in various fields (e.g., [22][23][24]). The Delphi method is [25] is based on the collection of data from the participants' field of expertise with the aim of achieving the consensus through a series of questionnaires.…”

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confidence: 99%

Planning an Intermodal Terminal for the Sustainable Transport Networks

et al. 2019

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Growing competition in the global market imposes the need for adequate planning of transportation processes and development of intermodal transport networks, whereby intermodal terminals play a key role. This paper proposes a methodology for prioritization of the intermodal terminal's development features, as the procedure in its planning process, leading to the design of the intermodal terminal in accordance with the needs of various stakeholders and the principles of the sustainable development. As the stakeholders often have conflicting interests and objectives, it is necessary to consider a broad set of requirements and developmental features that enable the fulfillment of the defined requirements. In order to solve the problem this paper proposes a new hybrid multi-criteria decision-making model that combines Delphi, Analytical Network Process (ANP) and Quality Function Deployment (QFD) methods in the fuzzy environment. The applicability of the proposed model is demonstrated by solving an example of planning an intermodal terminal in Belgrade.Sustainability 2019, 11, 4102 2 of 20 gained substantial attention in recent years, in academic research (e.g., [5,6]), as well as in practice. For example, the European Union set the goals to shift 30% of the road freight transport over 300 km to other, more environmental friendly means of transport (such as rail and waterborne), by the year 2030, and more than 50% by 2050 [7]. These goals can be achieved only by more intensive development of the intermodal transport.One of the major subsystems of the intermodal transport is intermodal terminal representing the place of storage and transshipment of intermodal transport units between the different modes of transport [8]. Intermodal terminals play a significant role in achieving socio-economic and environmental sustainability [9], and their development has an impact on improving the competitive advantage in the market [10]. Accordingly, requirements, goals and needs of different stakeholders, such as investors, owners, operators of the terminal, terminal users, authorities and residents, have to be in taken into consideration in the process of intermodal terminal planning. Their demands are often conflicting; therefore, a solution that should fit all actors involved is the goal in the planning process. Thus far, the research in the area of intermodal transport planning focused mainly on finding the optimal location for intermodal terminals (e.g., [11][12][13]) or how to improve operational efficiency of inland intermodal terminals [14][15][16]. However, the research related to solving the intermodal terminal planning problems taking into consideration variety of methods is rather scarce. Papers dealing with terminal planning are mainly focused on the intermodal transport network planning or the selection of terminal location. Therefore, the purpose of this paper is to define a methodology that comprehensively examines the different stakeholders' requirements based on which it defines and prioritizes development features ...

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Improving the Management and Operational Success of the Third Party Logistics Industry in Taiwan: Application of Fuzzy Quality Function Deployment

Cited by 6 publications

References 67 publications

Markov-Chain Simulation-Based Analysis of Human Resource Structure: How Staff Deployment and Staffing Affect Sustainable Human Resource Strategy

Markov-Chain Simulation-Based Analysis of Human Resource Structure: How Staff Deployment and Staffing Affect Sustainable Human Resource Strategy

Research on Evaluating the Sustainable Operation of Rail Transit System Based on QFD and Fuzzy Clustering

Planning an Intermodal Terminal for the Sustainable Transport Networks

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