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1 – 10 of over 1000Valeria Belvedere, Herbert Kotzab and Elisa Martina Martinelli
This paper aims to explore the conditions in a business-to-business-to-consumer (B2B2C) context characterized by new technologies. Innovations enhance disintermediation and pursue…
Abstract
Purpose
This paper aims to explore the conditions in a business-to-business-to-consumer (B2B2C) context characterized by new technologies. Innovations enhance disintermediation and pursue sustainability goals that drive customers’ willingness to use eco-friendly delivery options, namely, parcel lockers – in e-commerce and their impacts in terms of communication and transparency along the supply network.
Design/methodology/approach
The study conducted an extensive survey in Italy and Germany, collecting 1,010 usable responses. Structural equation modelling was used to analyse the data with the aim of identifying the factors that drive customers’ willingness to use parcel lockers and the effect on customers’ behaviour as determined by the disclosure of information about the environmental performance of different delivery options.
Findings
The results highlight several factors affecting the willingness to use parcel lockers, namely, performance and effort expectancy, social influence, technology anxiety, hedonistic motivation and environmental knowledge. The results also demonstrate that the disclosure of information about the environmental performance of different delivery options influences customers’ behaviour.
Research limitations/implications
This paper faces several limitations, mostly related to the focus on just two countries, the use of cross-sectional data and the survey’s explicit reference to just one type of product. Nevertheless, the findings contribute to the discussion on the relevance of information sharing along the supply chain, providing favourable evidence in this regard. It also improves the stream of research concerning technology adoption in the context of e-commerce, highlighting factors that can lead consumers to use eco-friendly self-service technologies.
Practical implications
The results can support companies in understanding how they can design and manage the last mile of delivery to jointly achieve customer satisfaction, process efficiency and superior environmental performance.
Originality/value
This pioneering contribution studies the adoption of delivery solutions for e-commerce and its implications for the supply network.
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Muhammad Ayat, Sheheryar Mohsin Qureshi and Changwook Kang
The purpose of this study is to propose an improved framework for managing Private Participation in Infrastructure ICT (PPI-ICT) projects in the context of developing countries as…
Abstract
Purpose
The purpose of this study is to propose an improved framework for managing Private Participation in Infrastructure ICT (PPI-ICT) projects in the context of developing countries as the requirements to manage them are different in several aspects.
Design/methodology/approach
The framework has been proposed based on an exhaustive literature review and statistical analysis of the PPI-ICT projects’ data set using logistic regression, F-test and student’s t-test. The proposed framework was also applied to the PPI-ICT projects.
Findings
The framework is an extension to NTCP (novelty, technology, complexity and pace) approach by including extrinsic factors such as income of the country, climate risk, religious diversity, political stability, regularity quality and control of corruption. The proposed framework was used to analyze project characteristics and their external conditions in the context of developing countries. Based on the analyses, the authors have presented a detailed set of recommendations for project managers, practitioners and governments to improve the success rate of these projects.
Originality/value
The major contribution of this study is the framework, which encompasses the NTCP model as well as extrinsic characteristics of PPI-ICT projects. The proposed framework is meant to assist the project managers to comprehend the project characteristics and its external environment to identify an adequate approach for managing projects successfully.
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Pham Duc Tai, Krit Jinawat and Jirachai Buddhakulsomsiri
Distribution network design involves a set of strategic decisions in supply chains because of their long-term impacts on the total logistics cost and environment. To incorporate a…
Abstract
Purpose
Distribution network design involves a set of strategic decisions in supply chains because of their long-term impacts on the total logistics cost and environment. To incorporate a trade-off between financial and environmental aspects of these decisions, this paper aims to determine an optimal location, among candidate locations, of a new logistics center, its capacity, as well as optimal network flows for an existing distribution network, while concurrently minimizing the total logistics cost and gas emission. In addition, uncertainty in transportation and warehousing costs are considered.
Design/methodology/approach
The problem is formulated as a fuzzy multiobjective mathematical model. The effectiveness of this model is demonstrated using an industrial case study. The problem instance is a four-echelon distribution network with 22 products and a planning horizon of 20 periods. The model is solved by using the min–max and augmented ε-constraint methods with CPLEX as the solver. In addition to illustrating model’s applicability, the effect of choosing a new warehouse in the model is investigated through a scenario analysis.
Findings
For the applicability of the model, the results indicate that the augmented ε-constraint approach provides a set of Pareto solutions, which represents the ideal trade-off between the total logistics cost and gas emission. Through a case study problem instance, the augmented ε-constraint approach is recommended for similar network design problems. From a scenario analysis, when the operational cost of the new warehouse is within a specific fraction of the warehousing cost of third-party warehouses, the solution with the new warehouse outperforms that without the new warehouse with respective to financial and environmental objectives.
Originality/value
The proposed model is an effective decision support tool for management, who would like to assess the impact of network planning decisions on the performance of their supply chains with respect to both financial and environmental aspects under uncertainty.
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Nikunj Kumar Jain, Kaustov Chakraborty and Piyush Choudhary
The purpose of this study is to develop a conceptual framework to understand how industry 4.0 technologies can help firms building supply chain resilience (SCR). With the…
Abstract
Purpose
The purpose of this study is to develop a conceptual framework to understand how industry 4.0 technologies can help firms building supply chain resilience (SCR). With the increasing in turbulent business environment and other disruptive events, firms want to build robust and risk resilience supply chains. The study also explores the role of supply chain visibility (SCV) and environmental dynamism (ED) on the relationship between Industry 4.0 and SCR.
Design/methodology/approach
Survey data from 354 firms designated by the Indian Ministry of Petroleum and Natural Gas, as well as organizations that work with these oil and gas firms was analyzed with structural equation modelling, hierarchical linear regression and necessary conditions analysis.
Findings
The findings reveal that Industry 4.0 base technologies enable firms to develop and exploit SCV to build SCR. Furthermore, Industry 4.0 base technologies substantially correlate with SCV under the differential effect of ED, improving SCR.
Research limitations/implications
The cross-sectional data restrict the generalizability of the findings to other geographies and sectors.
Originality/value
This study can assist managers in making well-informed decisions about the strategic use of technology to increase SCV and foster resilient supply chains.
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Mohsen Jami, Hamidreza Izadbakhsh and Alireza Arshadi Khamseh
This study aims to minimize the cost and time of blood delivery in the whole blood supply chain network (BSCN) in disaster conditions. In other words, integrating all strategic…
Abstract
Purpose
This study aims to minimize the cost and time of blood delivery in the whole blood supply chain network (BSCN) in disaster conditions. In other words, integrating all strategic, tactical and operational decisions of three levels of blood collection, processing and distribution leads to satisfying the demand at the right time.
Design/methodology/approach
This paper proposes an integrated BSCN in disaster conditions to consider four categories of facilities, including temporary blood collection centers, field hospitals, main blood processing centers and medical centers, to optimize demand response time appropriately. The proposed model applies the location of all permanent and emergency facilities in three levels: blood collection, processing and distribution. Other essential decisions, including multipurpose facilities, emergency transportation, inventory and allocation, were also used in the model. The LP metric method is applied to solve the proposed bi-objective mathematical model for the BSCN.
Findings
The findings show that this model clarifies its efficiency in the total cost and blood delivery time reduction, which results in a low carbon transmission of the blood supply chain.
Originality/value
The researchers proposed an integrated BSCN in disaster conditions to minimize the cost and time of blood delivery. They considered multipurpose capabilities for facilities (e.g. field hospitals are responsible for the three purposes of blood collection, processing and distribution), and so locating permanent and emergency facilities at three levels of blood collection, processing and distribution, support facilities, emergency transportation and traffic on the route with pollution were used to present a new model.
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Punsara Hettiarachchi, Subodha Dharmapriya and Asela Kumudu Kulatunga
This study aims to minimize the transportation-related cost in distribution while utilizing a heterogeneous fixed fleet to deliver distinct demand at different geographical…
Abstract
Purpose
This study aims to minimize the transportation-related cost in distribution while utilizing a heterogeneous fixed fleet to deliver distinct demand at different geographical locations with a proper workload balancing approach. An increased cost in distribution is a major problem for many companies due to the absence of efficient planning methods to overcome operational challenges in distinct distribution networks. The problem addressed in this study is to minimize the transportation-related cost in distribution while using a heterogeneous fixed fleet to deliver distinct demand at different geographical locations with a proper workload balancing approach which has not gained the adequate attention in the literature.
Design/methodology/approach
This study formulated the transportation problem as a vehicle routing problem with a heterogeneous fixed fleet and workload balancing, which is a combinatorial optimization problem of the NP-hard category. The model was solved using both the simulated annealing and a genetic algorithm (GA) adopting distinct local search operators. A greedy approach has been used in generating an initial solution for both algorithms. The paired t-test has been used in selecting the best algorithm. Through a number of scenarios, the baseline conditions of the problem were further tested investigating the alternative fleet compositions of the heterogeneous fleet. Results were analyzed using analysis of variance (ANOVA) and Hsu’s MCB methods to identify the best scenario.
Findings
The solutions generated by both algorithms were subjected to the t-test, and the results revealed that the GA outperformed in solution quality in planning a heterogeneous fleet for distribution with load balancing. Through a number of scenarios, the baseline conditions of the problem were further tested investigating the alternative fleet utilization with different compositions of the heterogeneous fleet. Results were analyzed using ANOVA and Hsu’s MCB method and found that removing the lowest capacities trucks enhances the average vehicle utilization with reduced travel distance.
Research limitations/implications
The developed model has considered both planning of heterogeneous fleet and the requirement of work load balancing which are very common industry needs, however, have not been addressed adequately either individually or collectively in the literature. The adopted solution methodologies to solve the NP-hard distribution problem consist of metaheuristics, statistical analysis and scenario analysis are another significant contribution. The planning of distribution operations not only addresses operational-level decision, through a scenario analysis, but also strategic-level decision has also been considered.
Originality/value
The planning of distribution operations not only addresses operational-level decisions, but also strategic-level decisions conducting a scenario analysis.
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Eric Zanghi, Milton Brown Do Coutto Filho and Julio Cesar Stacchini de Souza
The current and modern electrical distribution networks, named smart grids (SGs), use advanced technologies to accomplish all the technical and nontechnical challenges naturally…
Abstract
Purpose
The current and modern electrical distribution networks, named smart grids (SGs), use advanced technologies to accomplish all the technical and nontechnical challenges naturally demanded by energy applications. Energy metering collecting is one of these challenges ranging from the most basic (i.e., visual assessment) to the expensive advanced metering infrastructure (AMI) using intelligent meters networks. The AMIs’ data acquisition and system monitoring environment require enhancing some routine tasks. This paper aims to propose a methodology that uses a distributed and sustainable approach to manage wide-range metering networks, focused on using current public or private telecommunication infrastructure, optimizing the implementation and operation, increasing reliability and decreasing costs.
Design/methodology/approach
Inspired by blockchain technology, a collaborative metering system architecture is conceived, managing massive data sets collected from the grid. The use of cryptography handles data integrity and security issues.
Findings
A robust proof-of-concept simulation results are presented concerning the resilience and performance of the proposed distributed remote metering system.
Originality/value
The methodology proposed in this work is an innovative AMI solution related to SGs. Regardless of the implementation, operation and maintenance of AMIs, the proposed solution is unique, using legacy and new technologies together in a reliable way.
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Ramin Rostamkhani and Thurasamy Ramayah
This chapter of the book seeks to use famous mathematical functions (statistical distribution functions) in evaluating and analyzing supply chain network data related to supply…
Abstract
This chapter of the book seeks to use famous mathematical functions (statistical distribution functions) in evaluating and analyzing supply chain network data related to supply chain management (SCM) elements in organizations. In other words, the main purpose of this chapter is to find the best-fitted statistical distribution functions for SCM data. Explaining how to best fit the statistical distribution function along with the explanation of all possible aspects of a function for selected components of SCM from this chapter will make a significant attraction for production and services experts who will lead their organization to the path of competitive excellence. The main core of the chapter is the reliability values related to the reliability function calculated by the relevant chart and extracting other information based on other aspects of statistical distribution functions such as probability density, cumulative distribution, and failure function. This chapter of the book will turn readers into professional users of statistical distribution functions in mathematics for analyzing supply chain element data.
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Liyi Zhang, Mingyue Fu, Teng Fei, Ming K. Lim and Ming-Lang Tseng
This study reduces carbon emission in logistics distribution to realize the low-carbon site optimization for a cold chain logistics distribution center problem.
Abstract
Purpose
This study reduces carbon emission in logistics distribution to realize the low-carbon site optimization for a cold chain logistics distribution center problem.
Design/methodology/approach
This study involves cooling, commodity damage and carbon emissions and establishes the site selection model of low-carbon cold chain logistics distribution center aiming at minimizing total cost, and grey wolf optimization algorithm is used to improve the artificial fish swarm algorithm to solve a cold chain logistics distribution center problem.
Findings
The optimization results and stability of the improved algorithm are significantly improved and compared with other intelligent algorithms. The result is confirmed to use the Beijing-Tianjin-Hebei region site selection. This study reduces composite cost of cold chain logistics and reduces damage to environment to provide a new idea for developing cold chain logistics.
Originality/value
This study contributes to propose an optimization model of low-carbon cold chain logistics site by considering various factors affecting cold chain products and converting carbon emissions into costs. Prior studies are lacking to take carbon emissions into account in the logistics process. The main trend of current economic development is low-carbon and the logistics distribution is an energy consumption and high carbon emissions.
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Amin Mojoodi, Saeed Jalalian and Tafazal Kumail
This research aims to determine the ideal fare for various aircraft itineraries by modeling prices using a neural network method. Dynamic pricing has been studied from the…
Abstract
Purpose
This research aims to determine the ideal fare for various aircraft itineraries by modeling prices using a neural network method. Dynamic pricing has been studied from the airline’s point of view, with a focus on demand forecasting and price differentiation. Early demand forecasting on a specific route can assist an airline in strategically planning flights and determining optimal pricing strategies.
Design/methodology/approach
A feedforward neural network was employed in the current study. Two hidden layers, consisting of 18 and 12 neurons, were incorporated to enhance the network’s capabilities. The activation function employed for these layers was tanh. Additionally, it was considered that the output layer’s functions were linear. The neural network inputs considered in this study were flight path, month of flight, flight date (week/day), flight time, aircraft type (Boeing, Airbus, other), and flight class (economy, business). The neural network output, on the other hand, was the ticket price. The dataset comprises 16,585 records, specifically flight data for Iranian airlines for 2022.
Findings
The findings indicate that the model achieved a high level of accuracy in approximating the actual data. Additionally, it demonstrated the ability to predict the optimal ticket price for various flight routes with minimal error.
Practical implications
Based on the significant alignment observed between the actual data and the tested data utilizing the algorithmic model, airlines can proactively anticipate ticket prices across all routes, optimizing the revenue generated by each flight. The neural network algorithm utilized in this study offers a valuable opportunity for companies to enhance their decision-making processes. By leveraging the algorithm’s features, companies can analyze past data effectively and predict future prices. This enables them to make informed and timely decisions based on reliable information.
Originality/value
The present study represents a pioneering research endeavor that investigates using a neural network algorithm to predict the most suitable pricing for various flight routes. This study aims to provide valuable insights into dynamic pricing for marketing researchers and practitioners.
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