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1 – 10 of 41This paper aims to propose the mechanism of cross-network effect embedded, which can help cross-border e-commerce (CBEC) platforms strengthen cooperative relationships with…
Abstract
Purpose
This paper aims to propose the mechanism of cross-network effect embedded, which can help cross-border e-commerce (CBEC) platforms strengthen cooperative relationships with sellers more equitably and effectively by using the network structural characteristics of the platforms themselves.
Design/methodology/approach
A two-stage evolutionary game model has been used to confirm the influence factors. The mathematical derivation of evolutionary game analysis is combined with the simulation method to examine the role of cross-network effect in cooperation. The evolutionary game model based on the cross-network effect is proposed to achieve better adaptability to the study of cooperation strategy from the two-sided market perspective.
Findings
The evolutionary game model captures the interactions of cross-network effect and the influence factors from a dynamic perspective. The cross-network effect has a certain substitution on the revenue-sharing rate of SMEs. CBEC platforms can enhance the connection between consumers and the website by improving the level of construction, which is a good way to attract sellers more cost-effectively and efficiently.
Research limitations/implications
This study provides a new method for the validation of the cross-network effect, especially when data collection is difficult. But this method is only a numerical simulation. So the conclusions still need to be further tested empirically. Besides, researchers are advised to explore the relationship between the added user scale and the cross-network effect in some specificCBEC platforms.
Practical implications
This study provides a new method for the validation of the cross-network effect, especially when data collection is difficult. But this method is only a numerical simulation. So the conclusions still need to be further tested empirically. Besides, researchers are advised to explore the relationship between the added user scale and the cross-network effect in some specific CBEC platforms.
Originality/value
Investigations that study cooperation strategy from the cross-network effect perspective in CBEC are limited. The research figured out which influence factors are affected by the cross-network effect in cooperation. A two-stage evolutionary game model was proposed to explain the interaction of the factors. The evolutionary game analysis with a simulation method was combined to highlight the role of cross-network effect on cooperation strategy to give a deeper investigation into the sustainable cooperation ofCBEC.
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Ramji Nagariya, Subhodeep Mukherjee, Manish Mohan Baral and Venkataiah Chittipaka
This research tries to find the blockchain-based resilience strategies that can help the supply chains of micro, small, and medium-sized enterprises (MSMEs) to recover from the…
Abstract
Purpose
This research tries to find the blockchain-based resilience strategies that can help the supply chains of micro, small, and medium-sized enterprises (MSMEs) to recover from the disruptions and work effectively in a resource-based view perspective.
Design/methodology/approach
Eight broad strategies and 32 sub-strategies are identified from the literature review. Delphi study was carried out, and detailed discussion with 16 experts helped in finalizing these strategies. Further, the best-worst method (BWM) prioritized these strategies.
Findings
The findings suggests that “building social capital,” improving “coordination capabilities,” “sensitivity towards market,” “flexibility in process and production,” “reduction in process and lead time,”and “having a resource efficiency and redundancy” are the top strategies on which the top management should focus to overcome the situations of disruptions and enhance performance of MSMEs.
Practical implications
The blockchain-based strategies will enable the companies in tracing the products from the company to customers. Further, the customers will be able to identify their manufacturers, the raw materials used in manufacturing, and the life and quality of raw used materials. Altogether the textile industry will become more sensitive toward environmental practices.
Originality/value
The previous research has not identified and evaluated the blockchain-based resilience strategies, and therefore this study tries to fill this gap. This study used a smaller sample from the experts, so the results may vary if the larger data set is used and hypothesis testing can be done.
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Jianping Zhang, Leilei Wang and Guodong Wang
With the rapid advancement in the automotive industry, the friction coefficient (FC), wear rate (WR) and weight loss (WL) have emerged as crucial parameters to measure the…
Abstract
Purpose
With the rapid advancement in the automotive industry, the friction coefficient (FC), wear rate (WR) and weight loss (WL) have emerged as crucial parameters to measure the performance of automotive braking systems, so the FC, WR and WL of friction material are predicted and analyzed in this work, with an aim of achieving accurate prediction of friction material properties.
Design/methodology/approach
Genetic algorithm support vector machine (GA-SVM) model is obtained by applying GA to optimize the SVM in this work, thus establishing a prediction model for friction material properties and achieving the predictive and comparative analysis of friction material properties. The process parameters are analyzed by using response surface methodology (RSM) and GA-RSM to determine them for optimal friction performance.
Findings
The results indicate that the GA-SVM prediction model has the smallest error for FC, WR and WL, showing that it owns excellent prediction accuracy. The predicted values obtained by response surface analysis are closed to those of GA-SVM model, providing further evidence of the validity and the rationality of the established prediction model.
Originality/value
The relevant results can serve as a valuable theoretical foundation for the preparation of friction material in engineering practice.
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Da’ad Ahmad Albalawneh and M.A. Mohamed
Using a real-time road network combined with historical traffic data for Al-Salt city, the paper aims to propose a new federated genetic algorithm (GA)-based optimization…
Abstract
Purpose
Using a real-time road network combined with historical traffic data for Al-Salt city, the paper aims to propose a new federated genetic algorithm (GA)-based optimization technique to solve the dynamic vehicle routing problem. Using a GA solver, the estimated routing time for 300 chromosomes (routes) was the shortest and most efficient over 30 generations.
Design/methodology/approach
In transportation systems, the objective of route planning techniques has been revised from focusing on road directors to road users. As a result, the new transportation systems use advanced technologies to support drivers and provide them with the road information they need and the services they require to reduce traffic congestion and improve routing problems. In recent decades, numerous studies have been conducted on how to find an efficient and suitable route for vehicles, known as the vehicle routing problem (VRP). To identify the best route, VRP uses real-time information-acquired geographical information systems (GIS) tools.
Findings
This study aims to develop a route planning tool using ArcGIS network analyst to enhance both cost and service quality measures, taking into account several factors to determine the best route based on the users’ preferences.
Originality/value
Furthermore, developing a route planning tool using ArcGIS network analyst to enhance both cost and service quality measures, taking into account several factors to determine the best route based on the users’ preferences. An adaptive genetic algorithm (GA) is used to determine the optimal time route, taking into account factors that affect vehicle arrival times and cause delays. In addition, ArcGIS' Network Analyst tool is used to determine the best route based on the user's preferences using a real-time map.
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The purpose of this paper is to extract electrochemical reaction kinetics parameters, such as Tafel slope, exchange current density and equilibrium potential, which cannot be…
Abstract
Purpose
The purpose of this paper is to extract electrochemical reaction kinetics parameters, such as Tafel slope, exchange current density and equilibrium potential, which cannot be directly measured, this study aims to propose an improved particle swarm optimization (PSO) algorithm.
Design/methodology/approach
In traditional PSO algorithms, each particle’s historical optimal solution is compared with the global optimal solution in each iteration step, and the optimal solution is replaced with a certain probability to achieve the goal of jumping out of the local optimum. However, this will to some extent undermine the (true) optimal solution. In view of this, this study has improved the traditional algorithm: at each iteration of each particle, the historical optimal solution is not compared with the global optimal solution. Instead, after all particles have iterated, the optimal solution is selected and compared with the global optimal solution and then the optimal solution is replaced with a certain probability. This to some extent protects the global optimal solution.
Findings
The polarization curve plotted by this equation is in good agreement with the experimental values, which demonstrates the reliability of this algorithm and provides a new method for measuring electrochemical parameters.
Originality/value
This study has improved the traditional method, which has high accuracy and can provide great support for corrosion research.
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Junlong Peng and Xiang-Jun Liu
This research is aimed to mainly be applicable to expediting engineering projects, uses the method of inverse optimization and the double-layer nested genetic algorithm combined…
Abstract
Purpose
This research is aimed to mainly be applicable to expediting engineering projects, uses the method of inverse optimization and the double-layer nested genetic algorithm combined with nonlinear programming algorithm, study how to schedule the number of labor in each process at the minimum cost to achieve an extremely short construction period goal.
Design/methodology/approach
The method of inverse optimization is mainly used in this study. In the first phase, establish a positive optimization model, according to the existing labor constraints, aiming at the shortest construction period. In the second phase, under the condition that the expected shortest construction period is known, on the basis of the positive optimization model, the inverse optimization method is used to establish the inverse optimization model aiming at the minimum change of the number of workers, and finally the optimal labor allocation scheme that meets the conditions is obtained. Finally, use algorithm to solve and prove with a case.
Findings
The case study shows that this method can effectively achieve the extremely short duration goal of the engineering project at the minimum cost, and provide the basis for the decision-making of the engineering project.
Originality/value
The contribution of this paper to the existing knowledge is to carry out a preliminary study on the relatively blank field of the current engineering project with a very short construction period, and provide a path for the vast number of engineering projects with strict requirements on the construction period to achieve a very short construction period, and apply the inverse optimization method to the engineering field. Furthermore, a double-nested genetic algorithm and nonlinear programming algorithm are designed. It can effectively solve various optimization problems.
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Ying Wang, Melissa Chapman, Louise Byrne, James Hill and Timothy Bartram
This case documents an innovative human resource management (HRM) practice adopted by an Australian organization in the energy sector, purposefully introducing lived experience…
Abstract
Purpose
This case documents an innovative human resource management (HRM) practice adopted by an Australian organization in the energy sector, purposefully introducing lived experience informed “mental health advocate” (MHA) roles into the organization, to address pressing mental health workforce issues. MHA roles provide experiential, first-hand knowledge of experiencing mental health issues, offering a novel, common-sense and impactful perspective on supporting employees with mental health challenges.
Approach
Data that informed this case came from desktop research using publicly available resources, as well as a series of conversations with four key stakeholders in the organization. This approach allowed insights into Energy Queensland’s journey towards establishing novel MHA roles to delineate the day-to-day work practice of these roles.
Contribution to Practice
This is a novel HRM practice that has only recently emerged outside of the mental health sector. We discuss key considerations that enabled the success of the roles, including taking an evolutionary perspective, obtaining support from senior executives and relevant stakeholders, making a long-term financial commitment, and providing autonomy and flexibility in role design. This is the first article that documents this innovative practice to offer new insights to HRM scholars, as well as practical guidelines to other organizations in addressing workforce mental health issues.
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Radha Subramanyam, Y. Adline Jancy and P. Nagabushanam
Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data…
Abstract
Purpose
Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.
Design/methodology/approach
Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.
Findings
Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.
Research limitations/implications
Other optimization techniques can be applied for WSN to analyze the performance.
Practical implications
Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.
Social implications
Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.
Originality/value
Literature survey is carried out to find the methods which give better performance.
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Widya Paramita, Rokhima Rostiani, Rahmadi Hidayat, Sahid Susilo Nugroho and Eddy Junarsin
Electric cars (EC) adoption represents a strategic action aimed at promoting environmental sustainability. Although Millennials and Gen Z represent the greatest potential market…
Abstract
Purpose
Electric cars (EC) adoption represents a strategic action aimed at promoting environmental sustainability. Although Millennials and Gen Z represent the greatest potential market for EC, their adoption remains low; thus, this study focused on examining the role of motive in predicting EC adoption intention within these two generations’ population. Built upon the fundamental motive framework, this research explores the motives that lead to EC adoption intention. Subsequently, this study aims to examine the role of performance expectancy as the mediating variable and EC attributes beliefs as the moderating variable that can promote EC adoption intention.
Design/methodology/approach
Both exploratory and confirmatory methods were used in this investigation. Using an exploratory approach, this research explores the fundamental motives and the attributes of EC that influence EC adoption intention. Using a confirmatory approach, this research tests the mediating role of performance expectancy. To collect the data, an online survey was administered to 260 young consumers in Indonesia.
Findings
The results of PLS-SEM analysis from the data revealed that self-protection, kin-care, status and affiliative motives influence EC adoption. Furthermore, performance expectancy mediates the relationship between self-protection, mate acquisition, affiliative motives and EC adoption intention. Among EC attributes, the short-haul performance strengthens the indirect relationship between affiliative motive and EC adoption intention.
Research limitations/implications
The main limitation of this study is that it only focuses on the practical attributes of EC, whereas psychological attributes that were found to be more influential in consumer’s purchase decisions were not examined.
Practical implications
Marketers need to explore EC attributes that can strengthen the relationship between consumers’ motives and EC adoption intention by increasing consumers’ evaluation of performance expectancy. In this study, marketers can promote short-haul performance, as it will lead to EC adoption for consumers with affiliative motives.
Originality/value
This study ties together two lines of research on the adoption of EC, exploring EC attributes and examining consumers’ motivation to choose EC, especially Millennials and Gen Z. In this way, EC attributes facilitate the fulfillment of consumers’ needs and promote EC adoption intention.
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Nicola Cobelli and Silvia Blasi
This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation…
Abstract
Purpose
This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation dimensions in the healthcare industry adoption studies.
Design/methodology/approach
We followed a mixed-method approach combining bibliometric methods and topic modeling, with 57 papers being deeply analyzed.
Findings
Our results identify three latent topics. The first one is related to the digitalization in healthcare with a specific focus on the COVID-19 pandemic. The second one groups up the word combinations dealing with the research models and their constructs. The third one refers to the healthcare systems/professionals and their resistance to ATI.
Research limitations/implications
The study’s sample selection focused on scientific journals included in the Academic Journal Guide and in the FT Research Rank. However, the paper identifies trends that offer managerial insights for stakeholders in the healthcare industry.
Practical implications
ATI has the potential to revolutionize the health service delivery system and to decentralize services traditionally provided in hospitals or medical centers. All this would contribute to a reduction in waiting lists and the provision of proximity services.
Originality/value
The originality of the paper lies in the combination of two methods: bibliometric analysis and topic modeling. This approach allowed us to understand the ATI evolutions in the healthcare industry.
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