Felix T.S. Chan, Nelson K.H. Tang, H.C.W Lau and R.W.L. Ip
Evaluates a simulation approach to measuring supply chain performance which incorporates order release theory. Within manufacturing a number of order release mechanisms have been…
Abstract
Evaluates a simulation approach to measuring supply chain performance which incorporates order release theory. Within manufacturing a number of order release mechanisms have been developed. The importance of order release is first examined and its applicability to monitoring the performance of the supply chain is proposed. A simulation model of a typical, single channel logistics network was developed. Using the simulation model, each of the order release mechanisms was assessed and close agreement was obtained with the work of previous researchers. A new order release approach is proposed which is found to be superior to those analysed previously and should lead to improved supply chain performance.
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F.T.S. Chan, M.H. Chan, H. Lau and R.W.L. Ip
This paper presents an overview and guidance for manufacturing companies which are preparing to invest in advanced manufacturing technology (AMT). The purpose of this paper is to…
Abstract
This paper presents an overview and guidance for manufacturing companies which are preparing to invest in advanced manufacturing technology (AMT). The purpose of this paper is to explain the reasons why the company may encounter problems while adopting AMT, and to look at the many suggestions offered by the relevant literature for improving the performance of evaluation in AMT investment. According to the four major steps in adopting AMT (i.e. strategic planning, justification, training and installation, and routinization and implementation), the research work here aims to assist managers or investors to recognize problems at each step, thus offering appropriate ways to avoid and/or solve those problems. It is believed that improved justification methods will encourage more firms to invest in AMT and to realize the benefits these investments can offer.
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Mahmut Bakır, Emircan Özdemir and Şahap Akan
Ground-handling services are important for effective aircraft operations in the air transportation system. Airlines often outsource these services to ground-handling agents…
Abstract
Purpose
Ground-handling services are important for effective aircraft operations in the air transportation system. Airlines often outsource these services to ground-handling agents through business-to-business (B2B) marketing decisions. Therefore, this paper aims to address the problem of ground-handling agent selection in the airline industry.
Design/methodology/approach
A real-world case study was carried out to demonstrate the applicability of the integrated best worst method and fuzzy multi-attribute ideal real comparative analysis (F-MAIRCA) approach to solve ground-handling agent selection problems under uncertainty and imprecision. A two-stage sensitivity analysis was also conducted to ensure the credibility and validity of the application.
Findings
In the weighting stage, “Quality” was determined as the most important criterion in terms of supplier performance. With regard to the performance of the ground-handling agents, A2 was found as the optimal supplier in terms of both credibility and validity.
Practical implications
This study enumerated several criteria that ground-handling agents must meet in order to effectively supply services for the airlines. In addition, this study provides a novel framework from which managers can gain additional benefits from their businesses. Finally, it is concluded that this approach will help airline managers quantitatively in choosing the most appropriate ground-handling agent.
Originality/value
The contributions of this study to the existing literature are twofold. First, we propose a novel multiple attribute decision-making approach to address the problem of supplier selection for airlines under uncertainty and imprecision. Second, the selection of ground-handling agents from the B2B perspective is addressed for the first time in literature.
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Henry C.W. Lau, Peter K.H. Lau, Richard Y.K. Fung, Felix T.S. Chan and Ralph W.L. Ip
This paper attempts to propose a virtual case‐based benchmarking system (VCBS) which incorporates computational intelligence technologies into partners' benchmarking process to…
Abstract
Purpose
This paper attempts to propose a virtual case‐based benchmarking system (VCBS) which incorporates computational intelligence technologies into partners' benchmarking process to support decision‐making.
Design/methodology/approach
The proposed system consists of three main modules: data repository module, OLAP module and case‐based reasoning (CBR) module. The VCBS is a web‐based application that enables users to access the system and submit information to the system in anywhere at anytime. The database repository, on the other hand, maintains and acquires the data that are generated in the transactions processes and other workflow processes. It also ensures the entire valuable data which are accessible for the management to make decisions. The OLAP and the CBR modules are considered as the brain of the VCBS. The CBR module is aimed for short‐listing candidate, while the OLAP module is utilized for benchmarking the short‐listed candidate.
Findings
The VCBS is particularly useful in situations where multiple supply chain partners are involved to achieve the common objective to produce the products to the best satisfaction of customer demands with the lowest possible cost.
Research limitations/implications
Since data warehouse does not update in real time it only performs update periodically during non‐office hours to avoid network traffic. The solution provided to the company may not be the most updated information.
Originality/value
The proposed system improves the current practice of partner selection by adopting the computational intelligence technologies into the traditional partner selection process with the assimilation of data repository, CBR and OLAP to form the integrated system for evaluation of potential partners prior to the final decision.
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Runyue Han, Hugo K.S. Lam, Yuanzhu Zhan, Yichuan Wang, Yogesh K. Dwivedi and Kim Hua Tan
Although the value of artificial intelligence (AI) has been acknowledged by companies, the literature shows challenges concerning AI-enabled business-to-business (B2B) marketing…
Abstract
Purpose
Although the value of artificial intelligence (AI) has been acknowledged by companies, the literature shows challenges concerning AI-enabled business-to-business (B2B) marketing innovation, as well as the diversity of roles AI can play in this regard. Accordingly, this study investigates the approaches that AI can be used for enabling B2B marketing innovation.
Design/methodology/approach
Applying a bibliometric research method, this study systematically investigates the literature regarding AI-enabled B2B marketing. It synthesises state-of-the-art knowledge from 221 journal articles published between 1990 and 2021.
Findings
Apart from offering specific information regarding the most influential authors and most frequently cited articles, the study further categorises the use of AI for innovation in B2B marketing into five domains, identifying the main trends in the literature and suggesting directions for future research.
Practical implications
Through the five identified domains, practitioners can assess their current use of AI and identify their future needs in the relevant domains in order to make appropriate decisions on how to invest in AI. Thus, the research enables companies to realise their digital marketing innovation strategies through AI.
Originality/value
The research represents one of the first large-scale reviews of relevant literature on AI in B2B marketing by (1) obtaining and comparing the most influential works based on a series of analyses; (2) identifying five domains of research into how AI can be used for facilitating B2B marketing innovation and (3) classifying relevant articles into five different time periods in order to identify both past trends and future directions in this specific field.
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Ajay Jha, R.R.K. Sharma, Vimal Kumar and Pratima Verma
A well-designed supply chain performance measurement system, should account for not only the capabilities and performance attributes of the focal firm but also its supply chain…
Abstract
Purpose
A well-designed supply chain performance measurement system, should account for not only the capabilities and performance attributes of the focal firm but also its supply chain partners. The purpose of this paper is to help design a system that strikes a balance between the strategic objectives of the focal firm and its supply partners vis-à-vis the requirements of supply chain performance (cost, quality, speed and customer taste).
Design/methodology/approach
A theoretical framework on the strategic supply chain performance measurement system is developed based on existing literature and subsequently tested using a survey on 136 successful manufacturing organizations in India. The organizations were clustered into three strategy types and compared using analysis of variance on ranks to look for differences in preference for performance parameters.
Findings
The study examined the five dimensions of the supply chain practices, namely, strategic supply/distribution network, customer relationship, internal operations, information sharing and social and environmental responsiveness. The empirical results demonstrate the inclusion of business strategy orientation in designing today’s supply chain and hence its performance measurement system. Not supported hypotheses were addressed in the light of contextual factors.
Research limitations/implications
The study is confined to finding preferences of non-financial aspects of supply chain performance and tier-1 suppliers. The research helps better design and benchmark supply chain performance metrics, based on the strategic choice of the firm.
Originality/value
This paper highlights the shortcomings in the existing performance measurement and gaps in the existing literature in the supply chain context. Further, it gives a holistic view of strategic supply chain performance measurement design.
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Narges Hemmati, Masoud Rahiminezhad Galankashi, D.M. Imani and Farimah Mokhatab Rafiei
The purpose of this paper is to select the best maintenance policy for different types of equipment of a manufacturer integrating the fuzzy analytic hierarchy process (FAHP) and…
Abstract
Purpose
The purpose of this paper is to select the best maintenance policy for different types of equipment of a manufacturer integrating the fuzzy analytic hierarchy process (FAHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) models.
Design/methodology/approach
The decision hierarchy of this research includes three levels. The first level aims to choose the best maintenance policy for different types of equipment of an acid manufacturer. These equipment pieces include molten sulfur ponds, boiler, absorption tower, cooling towers, converter, heat exchanger and sulfur fuel furnace. The second level includes decision criteria of added-value, risk level and the cost. Lastly, the third level comprises time-based maintenance (TBM), corrective maintenance (CM), shutdown maintenance and condition-based maintenance (CBM) as four maintenance policies.
Findings
The best maintenance policy for different types of equipment of a manufacturer is the main finding of this research. Based on the obtained results, CBM policy is suggested for absorption tower, boiler, cooling tower and molten sulfur ponds, TBM policy is suggested for converters and heat exchanger and CM policy is suggested for a sulfur fuel furnace.
Originality/value
This research develops a novel model by integrating FAHP and an interval TOPSIS with concurrent consideration of added-value, risk level and cost to select the best maintenance policy. According to the highlights of the previous studies conducted on maintenance policy selection and related tools and techniques, an operative integrated approach to combine risk, added-value and cost with integrated fuzzy models is not developed yet. The majority of the previous studies have considered classic fuzzy approaches such as FAHP, FANP, Fuzzy TOPSIS, etc., which are not completely capable to reflect the decision makers’ viewpoints.
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Tarwaji Warsokusumo, Toni Prahasto and Achmad Widodo
The study aims to perform an extensive literature review in the area of the maintenance decision analysis (MDA), especially in power generation systems. In the basis of this…
Abstract
Purpose
The study aims to perform an extensive literature review in the area of the maintenance decision analysis (MDA), especially in power generation systems. In the basis of this review, the paper proposes a new model for the MDA which involves a combination of reliability, availability, maintainability and safety (RAMS) performance with energy efficiency performance (EEP).
Design/methodology/approach
Starting from the opportunity in Sustainable Development Scenario (SDS) by improving the energy efficiency (EE) and using renewable energy for the power generation system, also concerning to the major challenge of maintenance optimization in order to implement maintenance strategy, the maintenance decision-making and energetic efficiency management system (EEMS) have been reviewed. In the context of power generation system's performance, the measurement is also analyzed and identified. Then, the extensive literature review has been performed to compare between RAMS and EEP. And finally, the limitation and gap, where EEP is not yet a complementary consideration during MDA being identified and a new model for the performance-based MDA is proposed.
Findings
The new model proposed for the performance-based MDA is able to be used to conduct maintenance decision by utilizing the combination of RAMS and EEP depending on the type of decision required.
Practical implications
There is an opportunity for a maintenance organization of power generation plant to apply this new model proposed for the MDA in order to optimize the maintenance scope and schedule.
Originality/value
The result of work in this paper forms the basis for combining RAMS with EEP as performance-based MDA tools in the context of maintenance of the power generation system.
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Md. Tanweer Ahmad and Sandeep Mondal
This paper aims to address the supplier selection (SS) problem under dynamic business environments to optimize the procurement cost of spare-parts in the context of a mining…
Abstract
Purpose
This paper aims to address the supplier selection (SS) problem under dynamic business environments to optimize the procurement cost of spare-parts in the context of a mining equipment company (MEC). Practically, involved parameters’ value does not remain constant as planning periods due to fluctuation in the demand and their market dynamics. Therefore, dynamicity in the parameter is considered as an important factor when a company forms a responsive chain through most eligible suppliers with respect to planning periods. This area of study may be considered for their complexities to the approaches toward order-allocations with bi-products of unused and repair spare-parts.
Design/methodology/approach
An integrated methodology of analytic hierarchy process (AHP) and mixed-integer non-linear programming (MILP) is implemented in the two stages during each planning periods. In the first stage, AHP is used to obtain the relative weights with respect to each spare-parts of each criterion and based on that, the ranking is evaluated in accordance with case considered. And in the second stage, MILP is formulated to find the allocations of each spare-part with two distinct approaches through Model-1 and Model-2 separately. Moreover, Model-1 and Model-2 are outlined based on the ranking and efficient parameters-value under cost, limited capacities, quality level and delay lead time respectively.
Findings
The ranking and their optimal order-allocation of potential suppliers are obtained during consecutive planning periods for both unused and repair spare-parts. Subsequently, sensitivity analysis is conducted to deduce the key nuggets with the comparison of Model-1 and Model-2 in the changing of capacity, demand and cost per spare-parts. From this analysis, it is found that suppliers who have optimal parameter settings would be better for order-allocations than ranking during the changing planning period.
Practical implications
This paper points out the situation-specific approach for SS problem for a mining industry which often faces disruptive supplying environments. The managerial implication between ranking and parameters are highlighted through Model-1 and Model-2 by sensitivity analysis.
Originality/value
It provides useful directions for managers who are involved in the procurement of spare-parts in the mining environment. For this, suppliers are selected for order-allocation by using Model-1 and Model-2 in the dynamic business environment. The solvability of the model is presented using LINGO 17. Furthermore, the case company selected in this study can be extended to other sectors.
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Chun‐Chin Wei, Tian‐Shy Liou and Kuo‐Liang Lee
The purpose of this paper is to propose a comprehensive framework for measuring the performance of an enterprise resource planning (ERP) system to survey suitable performance…
Abstract
Purpose
The purpose of this paper is to propose a comprehensive framework for measuring the performance of an enterprise resource planning (ERP) system to survey suitable performance indicators (PIs) according to knowledge of the ERP implementation objectives set up at the implementation phase and build consistent measurement standards for facilitating the complex ERP performance evaluation process.
Design/methodology/approach
A seven‐step ERP performance measurement framework based on the objectives of ERP implementation is proposed. A fuzzy ERP performance index is used to account for the ambiguities involved in evaluating the performance of the ERP system. The fuzzy ERP performance index can be translated first into simple scores and then back to linguistic terms. An actual example in Taiwan demonstrates the feasibility of applying the proposed framework.
Findings
The findings indicate that the PIs of ERP performance measurement should align with the objectives of ERP implementation. The assessment results can represent the achievement of these objectives and the directions for improving the adopted ERP system.
Originality/value
This study may be interesting to some academic researchers and practical managers. The proposed framework can provide a procedure to link the objectives identified in the ERP system implementation phase and the performance considerations in the ERP use phase.