4.5. Integrated approaches
Integrated approaches are also discussed in the literature and are generally used in the different stages of 3PL selection process such as the identification of important evaluation criteria, the elimination of unsuitable 3PL, and the final selection of the best 3PL. In this sense, 19 papers (28.36%) proposed these methods to tackle this process.
As per [69], an integrated approach combining AHP and MIP is applied to evaluate the performance of truck carriers. Nine sub-criteria are used and grouped into 3 main criteria: customer service (reliability, flexibility, quality, and facilities/equipment), pricing and rates (basic rates, and flexibility of rates), and strategic compatibility (long-term relationship, strategic fit, and continuous improvement).
Degraeve et al. [70] proposed a model that integrates MIP and TCO (Total Cost of Ownership) in the case of airline selection in Belgium. TCO is used to evaluate the cost, objective to minimize in the model, under the airline market share per destination, and the discounts offered by the airlines constraints.
Thakkar et al. [71] used an approach integrating ISM and ANP for a proper selection of 3PL in the case of food sector in India. Their model takes into account 15 criteria grouped into 4 areas like autonomous (readiness to work under the brand name of the contract-giving organization, necessary certifications), dependent (readiness to enter into a long-term contract, geographical cover-age, proactiveness/readiness to share experiences in system design and reconfiguration, trust worthiness, attitude toward open-book accounting, readiness to work under a computerized system), linkage (sound financial background, previous experience, trained
logistics personnel, availability of computer network), and driver/ independent (ability to react to the changing needs-flexibility, margins provided to contractor, attitude toward hygienic practices).
As per [72], a hybrid system combining Data Mining and CBR is proposed to assist 3PL on logistics strategy development in China. Through this system, 3PL performance is measured by 8 factors, namely: price, real time information, delivery accuracy, stock status, communication, customer service, reporting, and stock spacing.
To model uncertainty and inaccuracy of the criteria weights, Bottani and Rizzi [2] proposed a fuzzy TOPSIS method that they applied to the case of a company operating in the dairy products in Italy. The 12 criteria used are: breadth of services, business experience, characterization of service, compatibility, financial stability, flexibility, performance, price, physical equipment and information systems, quality, strategic attitude, and trust and fairness.
Işıklar et al. [73] suggested a hybrid intelligent decision support framework for 3PL selection in Turkey, which integrates CBR/RBR and MOP techniques in fuzzy environment. Two groups of criteria are used. The 1st group focuses on the strategic aspects of the 3PL and identifies them as follows: financial stability, successful track record, similar size, comparable culture, similar values and goals, and fit to develop a sustainable relationship. The 2nd group is developed to measure important aspects of the 3PL business in 5 main categories: information technology, performance, quality, cost, and services.
Almeida [74] proposed a multi criteria model for 3PL selection in Brazil based on utility function and ELECTRE method. The utility function is introduced to incorporate the uncertainty evaluation of criteria while ELECTRE tool determines the final selection of 3PL. The evaluating criteria considered are: cost, delivery time, and dependability.
As per [75], a hybrid approach is proposed to evaluate 3PL in the Turkish logistics sector. This approach included a fuzzy AHP method to determine the relative weights of evaluation criteria, and a fuzzy TOPSIS to achieve the final partner-ranking. Two dimensions of criteria are considered. The 1st one, named strategic dimension, includes similar values-goals, similar size, financial stability, comparable culture, successful track record, and a fit to develop a sustainable relationship. The 2nd one, named business excellence dimension contains technical expertise, performance, market knowledge, and managerial experience.
Efendigil et al. [76] proposed an integrated fuzzy AHP–ANN model for selecting 3PL in the context of reverse logistics. For such, 12 performance indicators are considered which are: on time delivery ratio, confirmed fill rate, service quality level, unit operation cost, capacity usage ratio, total order cycle time, system flexibility index, integration level index, increment in market share, research and development ratio, environmental expenditures, and customer satisfaction index.
As per [77], a hybrid model integrating CBR and NLP techniques is suggested to select suitable 3PL among 13 transporters and 12 freight forwarders, in the use of the reconfiguration of supply chain network in China. The performance criteria considered are related to cost, delivery, quality, services, flexibility, and relationship.
Liu and Wang [78] used an integrated fuzzy approach for the evaluation and selection of 3PL in Taiwan. This method consists of three different techniques: the Delphi method to identify important evaluation criteria, an inference method to eliminate unsuitable 3PL, and a LP model for the final selection. In this sense, 17 criteria are considered: logistics information system, customer service, on-time shipments/deliveries, capability to handle specific business requirements, responsiveness, and accessibility to contact persons in urgency are the most important criteria. However, price, experience in similar industry, service quality, and general reputation are not as important. The other criteria used are:
location, market share, logistics equipment, EDI capacity, continuous improvement, value-added services, and cultural fit.
Kannan et al. [79] proposed an integrated ISM–TOPSIS approach for the selection of reverse 3PL in fuzzy environment in the case of battery manufacturing industry in India. For this, 7 main criteria are considered which are: quality, delivery, cost, rejection rate, technical and engineering capability, inability to meet future requirement, and willingness and attitude.
As per [80], the authors suggested a hybrid multi-criteria approach for 3PL selection in Taiwanese airline, which combined three models: DEMATEL to construct the interrelationship between criteria, ANP to determine the criteria weights, and VIKOR to prioritize the 3PL. Therefore, 12 criteria are used and classified on 4 dimensions: compatibility (relationship, flexibility, information sharing), quality (knowledge and skills, customer's satisfaction, on time rate), cost (cost savings, flexibility in billing), and risk (labor union, loss of management, control, information security).
Sasikumar and Haq [81] applied a fuzzy VIKOR method to reverse 3PL selection for the case of battery recycling in India. The authors used the same evaluating factors and dataset as that used by authors as per [80] to illustrate their model.
Li et al. [82] used fuzzy sets to evaluate 3PL performance in terms of management success, business strength, service quality,
and business growth criteria. The model is represented by a LP model that maximized the comprehensive evaluation result of 3PL according to these criteria. That model is illustrated by a real case of an air conditioner manufacturer in China.
As per [83], the authors proposed a method that combines AHP, DEA and LP in order to support the multi-criteria evaluation and selection of 3PL. The 7 criteria considered in their proposal model are: reliability of quality, speed of service, flexibility, cost, equipment, operators' safety, and environmental safeguard. The validation of the model is focused on 3 sectors in Italy, namely: industry and defense, perishable products, and consumer goods.
Ho et al. [84] developed an integrated QFD and fuzzy AHP for 3PL selection and evaluation. The 6 main criteria considered are: cost, delivery, flexibility, quality, technology, and risk. The model is applied to the case of a supplier of hard disk components in China.
4.5. Integrated approaches
Integrated approaches are also discussed in the literature and are generally used in the different stages of 3PL selection process such as the identification of important evaluation criteria, the elimination of unsuitable 3PL, and the final selection of the best 3PL. In this sense, 19 papers (28.36%) proposed these methods to tackle this process.
As per [69], an integrated approach combining AHP and MIP is applied to evaluate the performance of truck carriers. Nine sub-criteria are used and grouped into 3 main criteria: customer service (reliability, flexibility, quality, and facilities/equipment), pricing and rates (basic rates, and flexibility of rates), and strategic compatibility (long-term relationship, strategic fit, and continuous improvement).
Degraeve et al. [70] proposed a model that integrates MIP and TCO (Total Cost of Ownership) in the case of airline selection in Belgium. TCO is used to evaluate the cost, objective to minimize in the model, under the airline market share per destination, and the discounts offered by the airlines constraints.
Thakkar et al. [71] used an approach integrating ISM and ANP for a proper selection of 3PL in the case of food sector in India. Their model takes into account 15 criteria grouped into 4 areas like autonomous (readiness to work under the brand name of the contract-giving organization, necessary certifications), dependent (readiness to enter into a long-term contract, geographical cover-age, proactiveness/readiness to share experiences in system design and reconfiguration, trust worthiness, attitude toward open-book accounting, readiness to work under a computerized system), linkage (sound financial background, previous experience, trained
logistics personnel, availability of computer network), and driver/ independent (ability to react to the changing needs-flexibility, margins provided to contractor, attitude toward hygienic practices).
As per [72], a hybrid system combining Data Mining and CBR is proposed to assist 3PL on logistics strategy development in China. Through this system, 3PL performance is measured by 8 factors, namely: price, real time information, delivery accuracy, stock status, communication, customer service, reporting, and stock spacing.
To model uncertainty and inaccuracy of the criteria weights, Bottani and Rizzi [2] proposed a fuzzy TOPSIS method that they applied to the case of a company operating in the dairy products in Italy. The 12 criteria used are: breadth of services, business experience, characterization of service, compatibility, financial stability, flexibility, performance, price, physical equipment and information systems, quality, strategic attitude, and trust and fairness.
Işıklar et al. [73] suggested a hybrid intelligent decision support framework for 3PL selection in Turkey, which integrates CBR/RBR and MOP techniques in fuzzy environment. Two groups of criteria are used. The 1st group focuses on the strategic aspects of the 3PL and identifies them as follows: financial stability, successful track record, similar size, comparable culture, similar values and goals, and fit to develop a sustainable relationship. The 2nd group is developed to measure important aspects of the 3PL business in 5 main categories: information technology, performance, quality, cost, and services.
Almeida [74] proposed a multi criteria model for 3PL selection in Brazil based on utility function and ELECTRE method. The utility function is introduced to incorporate the uncertainty evaluation of criteria while ELECTRE tool determines the final selection of 3PL. The evaluating criteria considered are: cost, delivery time, and dependability.
As per [75], a hybrid approach is proposed to evaluate 3PL in the Turkish logistics sector. This approach included a fuzzy AHP method to determine the relative weights of evaluation criteria, and a fuzzy TOPSIS to achieve the final partner-ranking. Two dimensions of criteria are considered. The 1st one, named strategic dimension, includes similar values-goals, similar size, financial stability, comparable culture, successful track record, and a fit to develop a sustainable relationship. The 2nd one, named business excellence dimension contains technical expertise, performance, market knowledge, and managerial experience.
Efendigil et al. [76] proposed an integrated fuzzy AHP–ANN model for selecting 3PL in the context of reverse logistics. For such, 12 performance indicators are considered which are: on time delivery ratio, confirmed fill rate, service quality level, unit operation cost, capacity usage ratio, total order cycle time, system flexibility index, integration level index, increment in market share, research and development ratio, environmental expenditures, and customer satisfaction index.
As per [77], a hybrid model integrating CBR and NLP techniques is suggested to select suitable 3PL among 13 transporters and 12 freight forwarders, in the use of the reconfiguration of supply chain network in China. The performance criteria considered are related to cost, delivery, quality, services, flexibility, and relationship.
Liu and Wang [78] used an integrated fuzzy approach for the evaluation and selection of 3PL in Taiwan. This method consists of three different techniques: the Delphi method to identify important evaluation criteria, an inference method to eliminate unsuitable 3PL, and a LP model for the final selection. In this sense, 17 criteria are considered: logistics information system, customer service, on-time shipments/deliveries, capability to handle specific business requirements, responsiveness, and accessibility to contact persons in urgency are the most important criteria. However, price, experience in similar industry, service quality, and general reputation are not as important. The other criteria used are:
location, market share, logistics equipment, EDI capacity, continuous improvement, value-added services, and cultural fit.
Kannan et al. [79] proposed an integrated ISM–TOPSIS approach for the selection of reverse 3PL in fuzzy environment in the case of battery manufacturing industry in India. For this, 7 main criteria are considered which are: quality, delivery, cost, rejection rate, technical and engineering capability, inability to meet future requirement, and willingness and attitude.
As per [80], the authors suggested a hybrid multi-criteria approach for 3PL selection in Taiwanese airline, which combined three models: DEMATEL to construct the interrelationship between criteria, ANP to determine the criteria weights, and VIKOR to prioritize the 3PL. Therefore, 12 criteria are used and classified on 4 dimensions: compatibility (relationship, flexibility, information sharing), quality (knowledge and skills, customer's satisfaction, on time rate), cost (cost savings, flexibility in billing), and risk (labor union, loss of management, control, information security).
Sasikumar and Haq [81] applied a fuzzy VIKOR method to reverse 3PL selection for the case of battery recycling in India. The authors used the same evaluating factors and dataset as that used by authors as per [80] to illustrate their model.
Li et al. [82] used fuzzy sets to evaluate 3PL performance in terms of management success, business strength, service quality,
and business growth criteria. The model is represented by a LP model that maximized the comprehensive evaluation result of 3PL according to these criteria. That model is illustrated by a real case of an air conditioner manufacturer in China.
As per [83], the authors proposed a method that combines AHP, DEA and LP in order to support the multi-criteria evaluation and selection of 3PL. The 7 criteria considered in their proposal model are: reliability of quality, speed of service, flexibility, cost, equipment, operators' safety, and environmental safeguard. The validation of the model is focused on 3 sectors in Italy, namely: industry and defense, perishable products, and consumer goods.
Ho et al. [84] developed an integrated QFD and fuzzy AHP for 3PL selection and evaluation. The 6 main criteria considered are: cost, delivery, flexibility, quality, technology, and risk. The model is applied to the case of a supplier of hard disk components in China.
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