As an integrated part in supply chain,third-party logistics(3PL)has intrinsic connections with upstream manufacturer and downstream retailer.Using a Stackelberg game model consisting of a manufacturer,a retailer and a...As an integrated part in supply chain,third-party logistics(3PL)has intrinsic connections with upstream manufacturer and downstream retailer.Using a Stackelberg game model consisting of a manufacturer,a retailer and a 3PL to explicitly capture the interaction of firms’operations decisions,this paper attempts to better understand the role of integrated logistics and procurement service(ILPS)provided by a 3PL firm in supply chain management.Compared with a supply chain without ILPS,a Pareto region,in which all the supply chain members benefit from working with a 3PL firm offering ILPS,is disclosed.We also show that the Pareto region is more likely to occur with higher demand uncertainty.Finally,we reveal that the manufacturer obtains the highest profit in the Pareto region,and that the retailer can improve his profit share as the standard deviation of demand increases.展开更多
Treatment plan selection is a complex process because it sometimes needs sufficient experience and clinical information.Nowadays it is even harder for doctors to select an appropriate treatment plan for certain patien...Treatment plan selection is a complex process because it sometimes needs sufficient experience and clinical information.Nowadays it is even harder for doctors to select an appropriate treatment plan for certain patients since doctors might encounter difficulties in obtaining the right information and analyzing the diverse clinical data.In order to improve the effectiveness of clinical decision making in complicated information system environments,we first propose a linked data-based approach for treatment plan selection.The approach integrates the patients’clinical records in hospitals with open linked data sources out of hospitals.Then,based on the linked data net,treatment plan selection is carried on aided by similar historical therapy cases.Finally,we reorganize the electronic medical records of 97 colon cancer patients using the linked data model and count the similarity of these records to help treatment selecting.The experiment shows the usability of our method in supporting clinical decisions.展开更多
The work considers modification of the Best–Worst Scaling(BWS)to the so-called System 1(S1)approach.S1 was described by D.Kahneman as a spontaneous and automatic reaction by an unconsciousway in which human decision-...The work considers modification of the Best–Worst Scaling(BWS)to the so-called System 1(S1)approach.S1 was described by D.Kahneman as a spontaneous and automatic reaction by an unconsciousway in which human decision-makers choose among multiple alternatives.Application of S1 can be seen as a simplified BWS for data eliciting and express analysis of prioritization between many compared items.In S1,a respondent picks the items with which she feels“happy”,and those can be one,several,all,or none items in a task.Estimation of utilities is performed by multinomial-logit modeling with different optimization criteria which produce parameters of the models and choice probabilities of the items.Numerical examples by marketing research data are encouraging and demonstrating that spontaneous choice decisions can make S1 approach very fast,efficient,and convenient for express analysis of items prioritization,especially for big data.展开更多
One of the standout problems in rural regions of India is the lack of a comprehensive medical record system.Medical records are a vital part of any diagnosis as they provide a glimpse into the patient’s past,which is...One of the standout problems in rural regions of India is the lack of a comprehensive medical record system.Medical records are a vital part of any diagnosis as they provide a glimpse into the patient’s past,which is influential to the current diagnosis.Medical records help practitioners spot anomalies and patterns in a variety of medical cases.It is also utilized to gain a better understanding of the health situation in certain demographics.In this paper,the authors have proposed a comprehensive distributed system which can be used to preserve the medical history of individuals,and also provide a valuable insight into the health situation of the rural populous.The distributed data are aggregated into a single entity from which observations are gathered.The data acquired could be of extreme importance to the government,as it can be utilized to determine the health issues which require immediate attention,and to evaluate possible mitigation plans.The data collected would be portable and easily accessible with the help of mobile devices.展开更多
vip Editors(in alphabetical order)Michael Haenlein,ESCP Europe Business School,Paris,France Andreas Kaplan,ESCP Europe Business School,Berlin,Germany Chee-Wee Tan,Copenhagen Business School(CBS),Copenhagen,Denmark P...vip Editors(in alphabetical order)Michael Haenlein,ESCP Europe Business School,Paris,France Andreas Kaplan,ESCP Europe Business School,Berlin,Germany Chee-Wee Tan,Copenhagen Business School(CBS),Copenhagen,Denmark Pengzhu Zhang,Shanghai Jiao Tong University,China Artificial Intelligence(AI),defined as“a system’s ability to correctly interpret external data,to learn from such data and to use those learnings to achieve specific goals and tasks through flexible adaptation”(Kaplan&Haenlein,2019).展开更多
In this article,the authors propose a modified version of S.L.Chen and Liu’s model with a two-stage production system.Assume that the retailer’s order quantity is concerned with the manufacturer’s selling price and...In this article,the authors propose a modified version of S.L.Chen and Liu’s model with a two-stage production system.Assume that the retailer’s order quantity is concerned with the manufacturer’s selling price and the warranty period of product.The used cost of the customer is measured under the Taguchi’s quadratic quality loss function and concluded in the retailer’s profit function.The quality of the lot for the manufacturer is determined by adopting a two-stage single sampling rectifying inspection plan.The modified economic manufacturing quantity(EMQ)model is addressed in formulating the manufacturer’s expected profit.The retailer’s order quantity,manufacturer’s wholesale price,production run length,process mean,and warranty period of product will be jointly determined by maximizing the total expected profit of the supply chain system including the manufacturer and the retailer.Finally,the quality investment policy is introduced to illustrate the profit improvement for the supply chain system.展开更多
This paper explores a fuzzy analytic network process(FANP)approach in identifying the content of manufacturing strategy infrastructural decisions that integrates sustainability and classical manufacturing strategy fra...This paper explores a fuzzy analytic network process(FANP)approach in identifying the content of manufacturing strategy infrastructural decisions that integrates sustainability and classical manufacturing strategy framework with firm size component.The findings are as follows:(1)firms must ensure highquality product requirements with a make-to-order production system;(2)large firms must prioritize decentralization of functional areas but they must also provide higher systems integration of all production-related information to mobilize better communication channels;(3)large firms must employ highly skilled human resources in order to provide strong support on functional areas;and(4)small and medium enterprises must focus on product introduction to the market as a strategy priority area.The main contribution of this paper is the decision-making framework under uncertainty that holistically identifies the decisions that comprise a sustainable manufacturing strategy which may serve as guidelines in improving existing sustainable manufacturing practices or in creating new ones.展开更多
Artificial Intelligence has been playing a profound role in the global economy,social progress,and people’s daily life.With the increasing capabilities and accuracy of AI,the application of AI will have more impacts ...Artificial Intelligence has been playing a profound role in the global economy,social progress,and people’s daily life.With the increasing capabilities and accuracy of AI,the application of AI will have more impacts on manufacturing and service areas in the era of industry 4.0.This study conducts a systematic literature review to study the state-of-the-art on AI in industry 4.0.This paper describes the development of industries and the evolution of AI.This paper also identifies that the development and application of AI will bring not only opportunities but also challenges to industry 4.0.The findings provide a valuable reference for researchers and practitioners through a multi-angle systematic analysis of AI.In the era of industry 4.0,AI system will become an innovative and revolutionary assistance to the whole industry.展开更多
This paper aims to identify the antecedents of buying behavior for secondhand clothing among millennials,as well as to determine their underlying causal relationships.Upon a comprehensive literature search,a total of ...This paper aims to identify the antecedents of buying behavior for secondhand clothing among millennials,as well as to determine their underlying causal relationships.Upon a comprehensive literature search,a total of 18 antecedents were found,and these are categorized into three motives,namely,economic,hedonic and recreational,and critical.As a case study in the Philippines,a focus group discussion among experts who are active millennial secondhand clothing users and buyers were tasked to identify the antecedents they have experienced and further confirm those extracted from the literature.To establish the causal relationships of these antecedents,categorize them into net causes or net effects,and address the vagueness associated with the decision-making process,a fuzzy DEMATEL method is used.Results reveal that avoidance of conventional channels proves to be the antecedent providing the highest impact among all other antecedents.Uniqueness,high quality,and fashion trend found to be the antecedents with the highest impacts received,making them the major net effects.Findings from this work hope to provide a framework among practitioners that would lead to a better understanding of millennials’buying behavior for secondhand clothing.展开更多
Smart City is an emerging concept in global urban development.A Smart City applies ICT technologies to provide greater efficiencies for its urban areas and civilian population.One of the key requirements for a Smart C...Smart City is an emerging concept in global urban development.A Smart City applies ICT technologies to provide greater efficiencies for its urban areas and civilian population.One of the key requirements for a Smart City is to exploit data from its ICT infrastructure(such as Internet of Things connected sensors)to improve city services and features such as accessibility and sustainability.To address this requirement,the City of Melbourne(COM)Smart City office maintains several hundred data sets relating to urban activity and development.These datasets address parking,mobility,land use,3D data,statistics,environment,and major city developments such as rail projects.One promising dataset relates to pedestrian traffic.Data are obtained from sensors and updated on the COM website(City of Melbourne Open Data Platform:https://data.melbourne.vic.gov.au/.)at regular intervals.These data include the number of pedestrians passing 53 specific locations in the central business district and also their times and directions of travel.In a 24 h period,over 650,000 pedestrians were counted passing all locations.Peak rates of several thousand pedestrians per minute are regularly recorded during city rush hours at hotspots making the data amenable to Big Data analysis techniques.Results are obtained in graphical format as heatmaps and charts of city pedestrian traffic using both Microsoft Excel^(■)for static analysis and PowerBI^(■)for more advanced interactive visualisation and analysis.These findings can identify pedestrian hotspots and inform future locations of traffic lights and street configurations to make the city more pedestrian friendly.Further,the experience gained can be used to examine other data sets such as bicycle traffic that can be analysed to inform city infrastructure projects.Future work is suggested that could link these pedestrian flow data with social media data from smartphones and potentially wearable devices such as fitness monitors to correlate pedestrian satisfaction with traffic flow.The‘happiness’effect of pedestrians passing through green areas such as city parks can also be quantified.This research was undertaken with the assistance of Swinburne University under its Capstone Project scheme.展开更多
Student attrition remains a significant challenge for higher education institutions,particularly during the freshman to sophomore year transition.This study introduces a comprehensive decision-support framework that i...Student attrition remains a significant challenge for higher education institutions,particularly during the freshman to sophomore year transition.This study introduces a comprehensive decision-support framework that integrates stateof-the-art predictive machine learning(ML)techniques,local ML explanation techniques,and Generative AI to enhance individualized intervention programs aimed at reducing freshman student attrition.Utilizing a dataset encompassing 13 years of enrollment data from a sizable US academic institution,we developed predictive models using deep neural networks to identify students at risk of leaving school with an overall accuracy of 86%.SHapley Additive exPlanations(SHAP)was then used to enhance the transparency of the model by providing granular insights into the contribution of various factors to individual students'dropout risks.Notably,we employed Generative AI to translate SHAP scores into comprehensible and actionable intervention recommendations presented via an interactive decision-support dashboard.展开更多
This paper proposes a decision support system based on a machine-learned Bayesian network(BN)to predict the success rate of telemarketing calls for long-term bank deposits.Telemarketing is one of the most common inter...This paper proposes a decision support system based on a machine-learned Bayesian network(BN)to predict the success rate of telemarketing calls for long-term bank deposits.Telemarketing is one of the most common interactive techniques of direct marketing,widely used by financial institutions such as banks to sell long-term deposits.In this study,we develop a BN model that predicts the likelihood that a potential client subscribes to a long-term deposit,which is considered an output variable.The causal relationship among client attributes and outcomes has been identified using the augmented Naïve Bayes approach,a well-known supervised learning algorithm.The impact of each client’s attribute on the likelihood of subscribing is predicted.Further,we carry out multiple simulation scenarios using BN’s unique features(forward and backward propagation)to provide more in-depth discussions and analysis on predicting the likelihood of subscription for clients with particular characteristics.展开更多
In the present era of big data,web page searching and ranking in an efficient manner on the World Wide Web to satisfy the specific search needs of the modern user is undoubtedly a major challenge for search engines.Ev...In the present era of big data,web page searching and ranking in an efficient manner on the World Wide Web to satisfy the specific search needs of the modern user is undoubtedly a major challenge for search engines.Even though a large number of web search techniques have been developed,some problems still exist while searching with generic search engines as none of the search engines can index the entire web.The issue is not just the volume but also the relevance concerning the user’s requirements.Moreover,if the search query is partially incomplete or is ambiguous,then most of the modern search engines tend to return the result by interpreting all possible meanings of the query.Concerning search quality,more than half of the retrieved web pages have been reported to be irrelevant.Hence web search personalization is required to retrieve search results while incorporating the user’s interests.In the proposed research work we have highlighted the strengths and weakness of various studies as proposed in the literature for web search personalization by carrying out a detailed comparison among them.The in-depth comparative study with baselines leads to the recommendation of Intelligent Meta Search System(IMSS)and Advanced Cluster Vector Page Ranking(ACVPR)algorithm as one of the best approaches as proposed in the literature for web search personalization.Furthermore,the detailed discussion about the comparative analysis of all categories gives new opportunities to think in different research areas.展开更多
Effective mitigation of supply disruption is a crucial issue for many retailers.Although prior studies of supply disruption mainly focused on the sale of a single product,the bundling of products is one of the importa...Effective mitigation of supply disruption is a crucial issue for many retailers.Although prior studies of supply disruption mainly focused on the sale of a single product,the bundling of products is one of the important marketing tools that significantly impact businesses’profitability.In this study,we investigate a retailer who uses a dual-sourcing strategy for complementary products.The problem is formulated under different selling strategies,i.e.,separate selling,pure bundling,and mixed bundling.In each strategy,the concavity of the objective function is explored,and a solution algorithm is proposed.The results show that pure bundling is more sensitive to supply disruption than mixed bundling and separate selling.Actually,under pure bundling,the retailer transfers its sourcing strategy from dual to single sourcing even under a low probability of supply disruption.Furthermore,when bundle price elasticity is high,separate selling outperforms bundling and mixed bundling.展开更多
As the core driving force of the new round of informatization development and industrial revolution,the disruptive achievements of artificial intelligence(AI)are rapidly and comprehensively infiltrating into various f...As the core driving force of the new round of informatization development and industrial revolution,the disruptive achievements of artificial intelligence(AI)are rapidly and comprehensively infiltrating into various fields of human activities.Although technologies and applications of AI have been widely studied and factors that affect AI adoption are identified in existing literature,the impact of success factors on AI adoption remains unknown.Accordingly,this paper proposes a framework to explore the impacts of success factors on AI adoption in telecom industry by integrating the technology,organization,and environment(TOE)framework and diffusion of innovation(DOI)theory.Particularly,this framework consists of factors regarding external environment,organizational capabilities,and innovation attributes of AI.The framework is empirically tested with data collected by surveying telecom companies in China.Structural equation modeling is applied to analyze the data.The study provides support for firms’decision-making and resource allocation regarding AI adoption.展开更多
Spare parts management is a function of maintenance management that aims to support maintenance activities,giving real-time information on the available quantities of each spare part and adopting the inventory policie...Spare parts management is a function of maintenance management that aims to support maintenance activities,giving real-time information on the available quantities of each spare part and adopting the inventory policies that ensure their availability when required,minimizing costs.The classification of spare parts is crucial to control the vast number of parts that have different characteristics and specificities.Spare parts management involves mainly two areas,maintenance and logistics.Therefore,the integration of both input information is recommended to make decisions.This paper presents a multicriteria classification methodology combining maintenance and logistics perspectives that intends to differentiate and group spare parts to,subsequently,define the most appropriate stock management policy for each group.The methodology was developed based on a case study carried out in a multinational manufacturing company and is intended to be included in its computerized maintenance management system to support decision-making.展开更多
In times of unprecedented global disruption,such as the COVID-19 pandemic,the survival and recovery of firms depend not only on resources but also on leadership characteristics.This study explores whether CEOs’busine...In times of unprecedented global disruption,such as the COVID-19 pandemic,the survival and recovery of firms depend not only on resources but also on leadership characteristics.This study explores whether CEOs’business education is associated with firms’ability to navigate severe economic shocks and demonstrate corporate resilience.Using event-based analysis on 2,314 Chinese firms that faced sharp stock price declines,the research finds that firms led by CEOs with formal business education tend to experience smaller financial losses and faster recovery.These outcomes appear linked to financial management practices,such as higher cash holdings and more timely disposal of financial assets to manage liquidity pressures.Robustness checks confirm the consistency of the results,while additional analysis highlights that the association is stronger for CEOs with higher level of education.The study offers insights into how business-educated leadership relates to firms’adaptive capacity,providing useful implications for corporate governance,strategic decision-making,and post-pandemic recovery.展开更多
This work holistically evaluates the factors that can aid decision makers in finding the optimal location for food businesses in developing economies.It integrates the analytic hierarchy process(AHP)in determining cri...This work holistically evaluates the factors that can aid decision makers in finding the optimal location for food businesses in developing economies.It integrates the analytic hierarchy process(AHP)in determining criteria weights(i.e.benefit,opportunity,cost,risk)and the newly introduced three-way decision–Technique for Order Preference by Similarity to Ideal Solution(3WD-TOPSIS)method in identifying the priority factors.Applying the AHP yields the assignment of more priorities to benefits and opportunities rather than costs and risks,reflecting the benefit–or opportunity-oriented attitudes of food businesses.Meanwhile,the implementation of 3WD-TOPSIS results in the identification of government regulations and restrictions,proximity to consumers,parking capacity,supply chain strategy,and socio-economic status as the most crucial location decision factors.Findings from the comparative analyses show a high agreement between the results and those of other comparable methods.Managerial insights from these findings are outlined in this work.展开更多
In this study,two integrated game models are developed to explore the possible economic and environmental consequences of Emission control areas(ECA)regulations.Moreover,the analytical solutions compared with a benchm...In this study,two integrated game models are developed to explore the possible economic and environmental consequences of Emission control areas(ECA)regulations.Moreover,the analytical solutions compared with a benchmark case are derived.We find that vessel speed and SO_(2)emissions will decrease under the ECA regulations.However,shipping company’s level of competition has no effect on the equivalent speed.The equivalent freight volume to be reduced or increased is determined by the additional operational cost per voyage due to ECA regulations.Numerical study and sensitivity analysis reveal that the vessel speed and SO_(2)emission reduction are very sensitive to the inventory costs of intransit cargo.Furthermore,if low-sulphur marine gas oil is used throughout the voyage,the SO_(2)emission reduction may be greater than 80%,with a low impact on the shipping company’s profit.Thus,considering the environmental effects,much stricter limits can be set in the future.展开更多
Before mass production of individual components industries may assess its capability to produce it according to specifications.This capability assessment is a common requirement in the automotive sector.This work show...Before mass production of individual components industries may assess its capability to produce it according to specifications.This capability assessment is a common requirement in the automotive sector.This work shows a case study,providing an in-depth analysis,on a critical component and finds evidence of process degradation over two years of production,quantified through capability analysis.At pre-production,it was concluded that the process was capable and,thus,no statistical process control was done during its production.Over the months no defective units were detected but then its level began to increase and it was apparent that process variability had increased and the process was no longer capable.Process improvement activities were developed using known quality tools and methodologies.This work shows how the control plan initially defined became obsolete and discusses the need to periodically review quality control mechanisms.展开更多
基金We thank the financial support of National Natural Science Foundation of China(grant number 71531010).
文摘As an integrated part in supply chain,third-party logistics(3PL)has intrinsic connections with upstream manufacturer and downstream retailer.Using a Stackelberg game model consisting of a manufacturer,a retailer and a 3PL to explicitly capture the interaction of firms’operations decisions,this paper attempts to better understand the role of integrated logistics and procurement service(ILPS)provided by a 3PL firm in supply chain management.Compared with a supply chain without ILPS,a Pareto region,in which all the supply chain members benefit from working with a 3PL firm offering ILPS,is disclosed.We also show that the Pareto region is more likely to occur with higher demand uncertainty.Finally,we reveal that the manufacturer obtains the highest profit in the Pareto region,and that the retailer can improve his profit share as the standard deviation of demand increases.
基金This work was supported by the National Natural Science Foundation of China,[grant number 71171132,61373030].
文摘Treatment plan selection is a complex process because it sometimes needs sufficient experience and clinical information.Nowadays it is even harder for doctors to select an appropriate treatment plan for certain patients since doctors might encounter difficulties in obtaining the right information and analyzing the diverse clinical data.In order to improve the effectiveness of clinical decision making in complicated information system environments,we first propose a linked data-based approach for treatment plan selection.The approach integrates the patients’clinical records in hospitals with open linked data sources out of hospitals.Then,based on the linked data net,treatment plan selection is carried on aided by similar historical therapy cases.Finally,we reorganize the electronic medical records of 97 colon cancer patients using the linked data model and count the similarity of these records to help treatment selecting.The experiment shows the usability of our method in supporting clinical decisions.
文摘The work considers modification of the Best–Worst Scaling(BWS)to the so-called System 1(S1)approach.S1 was described by D.Kahneman as a spontaneous and automatic reaction by an unconsciousway in which human decision-makers choose among multiple alternatives.Application of S1 can be seen as a simplified BWS for data eliciting and express analysis of prioritization between many compared items.In S1,a respondent picks the items with which she feels“happy”,and those can be one,several,all,or none items in a task.Estimation of utilities is performed by multinomial-logit modeling with different optimization criteria which produce parameters of the models and choice probabilities of the items.Numerical examples by marketing research data are encouraging and demonstrating that spontaneous choice decisions can make S1 approach very fast,efficient,and convenient for express analysis of items prioritization,especially for big data.
基金This work was supported by the Department Science and Technology, India.
文摘One of the standout problems in rural regions of India is the lack of a comprehensive medical record system.Medical records are a vital part of any diagnosis as they provide a glimpse into the patient’s past,which is influential to the current diagnosis.Medical records help practitioners spot anomalies and patterns in a variety of medical cases.It is also utilized to gain a better understanding of the health situation in certain demographics.In this paper,the authors have proposed a comprehensive distributed system which can be used to preserve the medical history of individuals,and also provide a valuable insight into the health situation of the rural populous.The distributed data are aggregated into a single entity from which observations are gathered.The data acquired could be of extreme importance to the government,as it can be utilized to determine the health issues which require immediate attention,and to evaluate possible mitigation plans.The data collected would be portable and easily accessible with the help of mobile devices.
文摘vip Editors(in alphabetical order)Michael Haenlein,ESCP Europe Business School,Paris,France Andreas Kaplan,ESCP Europe Business School,Berlin,Germany Chee-Wee Tan,Copenhagen Business School(CBS),Copenhagen,Denmark Pengzhu Zhang,Shanghai Jiao Tong University,China Artificial Intelligence(AI),defined as“a system’s ability to correctly interpret external data,to learn from such data and to use those learnings to achieve specific goals and tasks through flexible adaptation”(Kaplan&Haenlein,2019).
文摘In this article,the authors propose a modified version of S.L.Chen and Liu’s model with a two-stage production system.Assume that the retailer’s order quantity is concerned with the manufacturer’s selling price and the warranty period of product.The used cost of the customer is measured under the Taguchi’s quadratic quality loss function and concluded in the retailer’s profit function.The quality of the lot for the manufacturer is determined by adopting a two-stage single sampling rectifying inspection plan.The modified economic manufacturing quantity(EMQ)model is addressed in formulating the manufacturer’s expected profit.The retailer’s order quantity,manufacturer’s wholesale price,production run length,process mean,and warranty period of product will be jointly determined by maximizing the total expected profit of the supply chain system including the manufacturer and the retailer.Finally,the quality investment policy is introduced to illustrate the profit improvement for the supply chain system.
基金The support provided by the University of San Carlos in terms of resource use is also recognized.
文摘This paper explores a fuzzy analytic network process(FANP)approach in identifying the content of manufacturing strategy infrastructural decisions that integrates sustainability and classical manufacturing strategy framework with firm size component.The findings are as follows:(1)firms must ensure highquality product requirements with a make-to-order production system;(2)large firms must prioritize decentralization of functional areas but they must also provide higher systems integration of all production-related information to mobilize better communication channels;(3)large firms must employ highly skilled human resources in order to provide strong support on functional areas;and(4)small and medium enterprises must focus on product introduction to the market as a strategy priority area.The main contribution of this paper is the decision-making framework under uncertainty that holistically identifies the decisions that comprise a sustainable manufacturing strategy which may serve as guidelines in improving existing sustainable manufacturing practices or in creating new ones.
文摘Artificial Intelligence has been playing a profound role in the global economy,social progress,and people’s daily life.With the increasing capabilities and accuracy of AI,the application of AI will have more impacts on manufacturing and service areas in the era of industry 4.0.This study conducts a systematic literature review to study the state-of-the-art on AI in industry 4.0.This paper describes the development of industries and the evolution of AI.This paper also identifies that the development and application of AI will bring not only opportunities but also challenges to industry 4.0.The findings provide a valuable reference for researchers and practitioners through a multi-angle systematic analysis of AI.In the era of industry 4.0,AI system will become an innovative and revolutionary assistance to the whole industry.
文摘This paper aims to identify the antecedents of buying behavior for secondhand clothing among millennials,as well as to determine their underlying causal relationships.Upon a comprehensive literature search,a total of 18 antecedents were found,and these are categorized into three motives,namely,economic,hedonic and recreational,and critical.As a case study in the Philippines,a focus group discussion among experts who are active millennial secondhand clothing users and buyers were tasked to identify the antecedents they have experienced and further confirm those extracted from the literature.To establish the causal relationships of these antecedents,categorize them into net causes or net effects,and address the vagueness associated with the decision-making process,a fuzzy DEMATEL method is used.Results reveal that avoidance of conventional channels proves to be the antecedent providing the highest impact among all other antecedents.Uniqueness,high quality,and fashion trend found to be the antecedents with the highest impacts received,making them the major net effects.Findings from this work hope to provide a framework among practitioners that would lead to a better understanding of millennials’buying behavior for secondhand clothing.
基金The authors acknowledge the support of Dr Gilbert Ravalli from Swinburne University of Tech-nology with assistance in obtaining funding for a Capstone Project.
文摘Smart City is an emerging concept in global urban development.A Smart City applies ICT technologies to provide greater efficiencies for its urban areas and civilian population.One of the key requirements for a Smart City is to exploit data from its ICT infrastructure(such as Internet of Things connected sensors)to improve city services and features such as accessibility and sustainability.To address this requirement,the City of Melbourne(COM)Smart City office maintains several hundred data sets relating to urban activity and development.These datasets address parking,mobility,land use,3D data,statistics,environment,and major city developments such as rail projects.One promising dataset relates to pedestrian traffic.Data are obtained from sensors and updated on the COM website(City of Melbourne Open Data Platform:https://data.melbourne.vic.gov.au/.)at regular intervals.These data include the number of pedestrians passing 53 specific locations in the central business district and also their times and directions of travel.In a 24 h period,over 650,000 pedestrians were counted passing all locations.Peak rates of several thousand pedestrians per minute are regularly recorded during city rush hours at hotspots making the data amenable to Big Data analysis techniques.Results are obtained in graphical format as heatmaps and charts of city pedestrian traffic using both Microsoft Excel^(■)for static analysis and PowerBI^(■)for more advanced interactive visualisation and analysis.These findings can identify pedestrian hotspots and inform future locations of traffic lights and street configurations to make the city more pedestrian friendly.Further,the experience gained can be used to examine other data sets such as bicycle traffic that can be analysed to inform city infrastructure projects.Future work is suggested that could link these pedestrian flow data with social media data from smartphones and potentially wearable devices such as fitness monitors to correlate pedestrian satisfaction with traffic flow.The‘happiness’effect of pedestrians passing through green areas such as city parks can also be quantified.This research was undertaken with the assistance of Swinburne University under its Capstone Project scheme.
文摘Student attrition remains a significant challenge for higher education institutions,particularly during the freshman to sophomore year transition.This study introduces a comprehensive decision-support framework that integrates stateof-the-art predictive machine learning(ML)techniques,local ML explanation techniques,and Generative AI to enhance individualized intervention programs aimed at reducing freshman student attrition.Utilizing a dataset encompassing 13 years of enrollment data from a sizable US academic institution,we developed predictive models using deep neural networks to identify students at risk of leaving school with an overall accuracy of 86%.SHapley Additive exPlanations(SHAP)was then used to enhance the transparency of the model by providing granular insights into the contribution of various factors to individual students'dropout risks.Notably,we employed Generative AI to translate SHAP scores into comprehensible and actionable intervention recommendations presented via an interactive decision-support dashboard.
文摘This paper proposes a decision support system based on a machine-learned Bayesian network(BN)to predict the success rate of telemarketing calls for long-term bank deposits.Telemarketing is one of the most common interactive techniques of direct marketing,widely used by financial institutions such as banks to sell long-term deposits.In this study,we develop a BN model that predicts the likelihood that a potential client subscribes to a long-term deposit,which is considered an output variable.The causal relationship among client attributes and outcomes has been identified using the augmented Naïve Bayes approach,a well-known supervised learning algorithm.The impact of each client’s attribute on the likelihood of subscribing is predicted.Further,we carry out multiple simulation scenarios using BN’s unique features(forward and backward propagation)to provide more in-depth discussions and analysis on predicting the likelihood of subscription for clients with particular characteristics.
文摘In the present era of big data,web page searching and ranking in an efficient manner on the World Wide Web to satisfy the specific search needs of the modern user is undoubtedly a major challenge for search engines.Even though a large number of web search techniques have been developed,some problems still exist while searching with generic search engines as none of the search engines can index the entire web.The issue is not just the volume but also the relevance concerning the user’s requirements.Moreover,if the search query is partially incomplete or is ambiguous,then most of the modern search engines tend to return the result by interpreting all possible meanings of the query.Concerning search quality,more than half of the retrieved web pages have been reported to be irrelevant.Hence web search personalization is required to retrieve search results while incorporating the user’s interests.In the proposed research work we have highlighted the strengths and weakness of various studies as proposed in the literature for web search personalization by carrying out a detailed comparison among them.The in-depth comparative study with baselines leads to the recommendation of Intelligent Meta Search System(IMSS)and Advanced Cluster Vector Page Ranking(ACVPR)algorithm as one of the best approaches as proposed in the literature for web search personalization.Furthermore,the detailed discussion about the comparative analysis of all categories gives new opportunities to think in different research areas.
文摘Effective mitigation of supply disruption is a crucial issue for many retailers.Although prior studies of supply disruption mainly focused on the sale of a single product,the bundling of products is one of the important marketing tools that significantly impact businesses’profitability.In this study,we investigate a retailer who uses a dual-sourcing strategy for complementary products.The problem is formulated under different selling strategies,i.e.,separate selling,pure bundling,and mixed bundling.In each strategy,the concavity of the objective function is explored,and a solution algorithm is proposed.The results show that pure bundling is more sensitive to supply disruption than mixed bundling and separate selling.Actually,under pure bundling,the retailer transfers its sourcing strategy from dual to single sourcing even under a low probability of supply disruption.Furthermore,when bundle price elasticity is high,separate selling outperforms bundling and mixed bundling.
文摘As the core driving force of the new round of informatization development and industrial revolution,the disruptive achievements of artificial intelligence(AI)are rapidly and comprehensively infiltrating into various fields of human activities.Although technologies and applications of AI have been widely studied and factors that affect AI adoption are identified in existing literature,the impact of success factors on AI adoption remains unknown.Accordingly,this paper proposes a framework to explore the impacts of success factors on AI adoption in telecom industry by integrating the technology,organization,and environment(TOE)framework and diffusion of innovation(DOI)theory.Particularly,this framework consists of factors regarding external environment,organizational capabilities,and innovation attributes of AI.The framework is empirically tested with data collected by surveying telecom companies in China.Structural equation modeling is applied to analyze the data.The study provides support for firms’decision-making and resource allocation regarding AI adoption.
基金This work was supported by European Structural and Investment Funds in the FEDER component,through the Operational Competitiveness and Internationalization Programme(COMPETE 2020)[Project n°002814Funding Reference:POCI-01-0247-FEDER-002814]。
文摘Spare parts management is a function of maintenance management that aims to support maintenance activities,giving real-time information on the available quantities of each spare part and adopting the inventory policies that ensure their availability when required,minimizing costs.The classification of spare parts is crucial to control the vast number of parts that have different characteristics and specificities.Spare parts management involves mainly two areas,maintenance and logistics.Therefore,the integration of both input information is recommended to make decisions.This paper presents a multicriteria classification methodology combining maintenance and logistics perspectives that intends to differentiate and group spare parts to,subsequently,define the most appropriate stock management policy for each group.The methodology was developed based on a case study carried out in a multinational manufacturing company and is intended to be included in its computerized maintenance management system to support decision-making.
文摘In times of unprecedented global disruption,such as the COVID-19 pandemic,the survival and recovery of firms depend not only on resources but also on leadership characteristics.This study explores whether CEOs’business education is associated with firms’ability to navigate severe economic shocks and demonstrate corporate resilience.Using event-based analysis on 2,314 Chinese firms that faced sharp stock price declines,the research finds that firms led by CEOs with formal business education tend to experience smaller financial losses and faster recovery.These outcomes appear linked to financial management practices,such as higher cash holdings and more timely disposal of financial assets to manage liquidity pressures.Robustness checks confirm the consistency of the results,while additional analysis highlights that the association is stronger for CEOs with higher level of education.The study offers insights into how business-educated leadership relates to firms’adaptive capacity,providing useful implications for corporate governance,strategic decision-making,and post-pandemic recovery.
文摘This work holistically evaluates the factors that can aid decision makers in finding the optimal location for food businesses in developing economies.It integrates the analytic hierarchy process(AHP)in determining criteria weights(i.e.benefit,opportunity,cost,risk)and the newly introduced three-way decision–Technique for Order Preference by Similarity to Ideal Solution(3WD-TOPSIS)method in identifying the priority factors.Applying the AHP yields the assignment of more priorities to benefits and opportunities rather than costs and risks,reflecting the benefit–or opportunity-oriented attitudes of food businesses.Meanwhile,the implementation of 3WD-TOPSIS results in the identification of government regulations and restrictions,proximity to consumers,parking capacity,supply chain strategy,and socio-economic status as the most crucial location decision factors.Findings from the comparative analyses show a high agreement between the results and those of other comparable methods.Managerial insights from these findings are outlined in this work.
文摘In this study,two integrated game models are developed to explore the possible economic and environmental consequences of Emission control areas(ECA)regulations.Moreover,the analytical solutions compared with a benchmark case are derived.We find that vessel speed and SO_(2)emissions will decrease under the ECA regulations.However,shipping company’s level of competition has no effect on the equivalent speed.The equivalent freight volume to be reduced or increased is determined by the additional operational cost per voyage due to ECA regulations.Numerical study and sensitivity analysis reveal that the vessel speed and SO_(2)emission reduction are very sensitive to the inventory costs of intransit cargo.Furthermore,if low-sulphur marine gas oil is used throughout the voyage,the SO_(2)emission reduction may be greater than 80%,with a low impact on the shipping company’s profit.Thus,considering the environmental effects,much stricter limits can be set in the future.
基金This work has been supported by COMPETE:POCI-01-0145-FEDER-007043FCT–Fundação para a Ciência e Tecnologia within the Project Scope:UID/CEC/00319/2013.
文摘Before mass production of individual components industries may assess its capability to produce it according to specifications.This capability assessment is a common requirement in the automotive sector.This work shows a case study,providing an in-depth analysis,on a critical component and finds evidence of process degradation over two years of production,quantified through capability analysis.At pre-production,it was concluded that the process was capable and,thus,no statistical process control was done during its production.Over the months no defective units were detected but then its level began to increase and it was apparent that process variability had increased and the process was no longer capable.Process improvement activities were developed using known quality tools and methodologies.This work shows how the control plan initially defined became obsolete and discusses the need to periodically review quality control mechanisms.
