The advantages of a cloud computing service are cost advantages,availability,scalability,flexibility,reduced time to market,and dynamic access to computing resources.Enterprises can improve the successful adoption rate...The advantages of a cloud computing service are cost advantages,availability,scalability,flexibility,reduced time to market,and dynamic access to computing resources.Enterprises can improve the successful adoption rate of cloud computing services if they understand the critical factors.Tofind critical factors,this studyfirst reviewed the literature and established a three-layer hierarch-ical factor table for adopting a cloud computing service based on the Technology-Organization-Environment framework.Then,a hybrid method that combines two multi-criteria decision-making tools—called the Fuzzy Analytic Network Process method and the concept of VlseKriterijumska Optimizacija I Kompromisno Resenje acceptable advantage—was used to objectively identify critical factors for the adop-tion of a cloud computing service,replacing the subjective decision of the authors.The results of this study determinedfive critical factors,namely data access secur-ity,information transmission security,senior management support,fallback cloud management,and employee acceptance.Finally,the paper presents thefindings and implications of the study.展开更多
The aim of this paper is to present through information collected via qualitative analysis in order to provide an alternative perspective to classify critical factors and their correlations in the processes of degrada...The aim of this paper is to present through information collected via qualitative analysis in order to provide an alternative perspective to classify critical factors and their correlations in the processes of degradation of river basins in countries in development in an ordered way.This study was started with a bibliographical review for gathering relevant information about the main factors,which was submitted to specialists and related professionals via survey developed in a format of answers on Likert scale,with the analyses of data from the respondents as well as their contribution within sample assembly exploratory factorial analysis and the charge factor item from the questionnaire with usage of polychoric correlation matrix with which it is proposed to establish the ordering of the factors relevance as well as their correlations through parametric statistical analysis with the usage of a generalized model of partial credit which belongs to the family of the models for polyatomic gradual answers to the item response theory(IRT)and the applying of cluster analysis(ICLUST)with the usage of both alpha and omega coefficient for the estimation of the variables group,with the R tool.As a result,the present study aims to establish a comprehension of the main factors for the ordering of the actions and attention of public and private sectors towards the preservation of urban river basins.展开更多
Certain wild animals represent sentinels to address issues related to environmental pollution,since they can provide integrative data on both pollutant exposure and biological effects.Despite their technological benef...Certain wild animals represent sentinels to address issues related to environmental pollution,since they can provide integrative data on both pollutant exposure and biological effects.Despite their technological benefits,PBDEs are considered a threat to environmental health due to their persistence,toxicity,and capacity to be accumulated.These pollutants have been found geographically widespread in fish,particularly in predator species such as trout.The aim of this work is to critically review the applicability and usefulness of wild trout for assessing PBDEs in freshwater environments.Reviewed reports include data from highly industrialized areas as well as areas from remote regions with relatively low human activity,including European and North American great lakes and freshwater environments in Europe,Greenland,subarctic areas and Patagonia,respectively.A summary of relevant factors were grouped into organism-specific factors(food habits,age,size,lipid content,sex and reproduction,tissue type,mechanism of contaminant uptake and metabolism),and PBDE levels in the surrounding environment(sediment).Five wild trout species[rainbow trout(Oncorhynchus mykiss),brown trout(Salmo trutta),lake trout(Salvelinus namaycush),arctic char(Salvelinus alpinus),and brook trout(Salvelinus fontinalis)],collected worldwide within the 1994 to present time frame,were considered.Multivariate techniques(principal component analysis-PCA)and mapping approach,showed clear differences in geographic distribution patterns of PBDE levels in trout depending on the region studied:wild trout from European and North American great lakes have the highest PBDE loads.This pattern could be due to high industrial activity at these locations.A correlational approach used to explore intraspecific relationships between PBDE levels and morphometry,showed positive relationships only for brown trout.Further,brown trout showed the highest trout-to-sediment ratios,which is suggestive of a relatively greater capacity of this species to accumulate PBDEs in relation to sediment levels.Overall,results suggest that adult wild trout could be useful as a PBDE bioindicator.展开更多
Manufacturing industries are facing challenges in the implementation of agile manufacturing in their products and processes.Agility is widely accepted as a new competitive concept in the manufacturing sector in fulfil...Manufacturing industries are facing challenges in the implementation of agile manufacturing in their products and processes.Agility is widely accepted as a new competitive concept in the manufacturing sector in fulfilling varying customer demand. Thus,evaluation of agile manufacturing in industries has become a necessity. The success of an organisation depends on its ability to manage finding the critical success factors and give them special and continued attention in order to bring about high performance. This paper proposes a set of critical success factors(CSFs) for evaluating agile manufacturing considered appropriate for the manufacturing sector.The analytical hierarchy process(AHP) method is applied for prioritizing the success factors, by summarizing the opinions of experts. It is believed that the proposed CSFs enable and assist manufacturing industries to achieve a higher performance in agile manufacturing so as to increase competitiveness.展开更多
In improving the competitiveness of business organi sa tion in the 21st century, minimising cost and increasing productivity are no lon ger factors that could promise the success. The changes in customer trends whic h...In improving the competitiveness of business organi sa tion in the 21st century, minimising cost and increasing productivity are no lon ger factors that could promise the success. The changes in customer trends whic h focusing more on product or service customising, high quality and short delive ry times are additional crucial factors that organisation should be aware of. T hese factors have direct relations on how the management could utilise the capab ility of its supply chain management (SCM). The importance of SCM in organisati on specifically to manufacturer is to play a vital role in managing the flow of material and information along the chain from suppliers to customers. In a trad itional way, SCM is mainly manage by the production department in organisation b ut with the advancement in information technology, resulted the changes in worki ng environment. One of the ways that could be implemented in decision making p rocess in order to improve the effectiveness and efficiency of the decision is t hrough collaborative environment. Due to this situation, there is a need to rede sign the existing SCM in order to optimise its capability and functionality in t he way to ensure the organisation competitiveness is sustainable. A minor or ma jor alignment to SCM business processes should be done in order to streamline th e flow of information, which could also affect the flow of materials. Factors s uch as SCM operational, structural and even its managerial are among the issues that are critical in redesigning its business process. Each of these factors has its own attributes such as lead-times, complexity, frequency and organisationa l setting that could lead in improving organisational competitiveness. In additi on, by identifying these factors, it would help the management to plan and desig n the collaborative SCM that would effectively correspond to the changes in busi ness and customer trends. The intention of the paper is to promote a list of fa ctors and attributes, which are critical in redesigning an existing SCM in order to shift its environment to become collaborative SCM. By utilising these facto rs and attributes, a model for redesigning SCM into collaborative environment is currently developed by the author and will be used in the next stage of his res earch.展开更多
The purpose of this paper is to provide a structured literature review of cross-border e-logistics research,uncover existing gaps and opportunities,try to find practical strategies to balance logistics costs and servi...The purpose of this paper is to provide a structured literature review of cross-border e-logistics research,uncover existing gaps and opportunities,try to find practical strategies to balance logistics costs and service levels,and improve logistics efficiency and customer satisfaction for future cross-border e-logistics research.Meanwhile this paper also uses the real data to test the tradeoff between transportation and warehousing cost.In addition,regression empirical analysis is used to make up for the lack of empirical drawbacks of many articles in the field and the result can be instructive and referential for cross-border e-commerce enterprises to make decisions on weighing logistics cost and service level to improve logistics efficiency.展开更多
The development of urban underground space(UUS)is of great significance for sustainable urban development because it has potential to solve many urban problems.However,the development of UUS is limited because there a...The development of urban underground space(UUS)is of great significance for sustainable urban development because it has potential to solve many urban problems.However,the development of UUS is limited because there are still a lot of constraints and challenges.To better understand the constraining factors of developing UUS and improve the development and utilization of UUS,this study conducts a comprehensive survey of existing literature retrieved from the Web of Science Core Collection database.Five main constraining factors,including the limited geological conditions,high cost,lack of natural light and ventilation,high incidence,and difficulty in collecting data and information on UUS,have been discussed to better understand how they affect the development of UUS.Based on the survey,the critical success factors of developing UUS,such as the effective governance structure,planning system for integrating UUS into urban development,coordination of the design of ground and underground,delineation of land property rights of UUS,and application of information techniques in the use of UUS,have been identified and discussed.In addition,knowledge gaps in the studies on development of UUS have been identified.Finally,the research trends and future directions have been proposed for better understanding and practice of UUS development.展开更多
The tension cracks and joints in rock or soil slopes affect their failure stability.Prediction of rock or soil slope failure is one of the most challenging tasks in the earth sciences.The actual slopes consist of inho...The tension cracks and joints in rock or soil slopes affect their failure stability.Prediction of rock or soil slope failure is one of the most challenging tasks in the earth sciences.The actual slopes consist of inhomogeneous materials,complex morphology,and erratic joints.Most studies concerning the failure of rock slopes primarily focused on determining Factor of Safety(FoS)and Critical Slip Surface(CSS).In this article,the effect of inclined tension crack on a rock slope failure is studied numerically with Shear Strength Reduction Factor(SRF)method.An inclined Tension Crack(TC)influences the magnitude and location of the rock slope’s Critical Shear Strength Reduction Factor(CSRF).Certainly,inclined cracks are more prone to cause the failure of the slope than the vertical TC.Yet,all tension cracks do not lead to failure of the slope mass.The effect of the crest distance of the tension crack is also investigated.The numerical results do not show any significant change in the magnitude of CSRF unless the tip of the TC is very near to the crest of the slope.ATC is also replaced with a joint,and the results differ from the corresponding TC.These results are discussed regarding shear stress and Critical Slip Surface(CSS).展开更多
Industry 4.0 is expected to play a crucial role in improving energy management and personnel performance in power plants.Poor performance problem in maintaining power plants is the result of both human errors,human fa...Industry 4.0 is expected to play a crucial role in improving energy management and personnel performance in power plants.Poor performance problem in maintaining power plants is the result of both human errors,human factors and the poor implementation of automation in energy management.This problem can potentially be solved using artificial intelligence(AI)and an integrated management system(IMS).This article investigates the current challenges to improving personnel and energy management performance in power plants,identifies the critical success factors(CSFs)for an integrated intelligent framework,and develops an intelligent framework that enables power plants to improve performance.The theoretical basis is founded on a systematic literature review to locate 110 out of 3108 papers studied carefully to examine the performance architecture that best enables effective maintenance.The findings from this literature review are combined with expert judgment and the big data advantages of AI applications to develop an intelligent model.Data are collected from a power plant in Iraq.To ensure the reliability of the proposed model,various hypotheses are tested using structural equation modeling.The results confirm that the measurement model is acceptable,and that the hypotheses are supported and significant.A case study demonstrates the strong relationship and significance between big data of performance and the CSFs.It is hoped that this model will be adopted to enable performance improvement in power plants.展开更多
Prediction of mode I fracture toughness(KIC) of rock is of significant importance in rock engineering analyses. In this study, linear multiple regression(LMR) and gene expression programming(GEP)methods were used to p...Prediction of mode I fracture toughness(KIC) of rock is of significant importance in rock engineering analyses. In this study, linear multiple regression(LMR) and gene expression programming(GEP)methods were used to provide a reliable relationship to determine mode I fracture toughness of rock. The presented model was developed based on 60 datasets taken from the previous literature. To predict fracture parameters, three mechanical parameters of rock mass including uniaxial compressive strength(UCS), Brazilian tensile strength(BTS), and elastic modulus(E) have been selected as the input parameters. A cluster of data was collected and divided into two random groups of training and testing datasets.Then, different statistical linear and artificial intelligence based nonlinear analyses were conducted on the training data to provide a reliable prediction model of KIC. These two predictive methods were then evaluated based on the testing data. To evaluate the efficiency of the proposed models for predicting the mode I fracture toughness of rock, various statistical indices including coefficient of determination(R2),root mean square error(RMSE), and mean absolute error(MAE) were utilized herein. In the case of testing datasets, the values of R2, RMSE, and MAE for the GEP model were 0.87, 0.188, and 0.156,respectively, while they were 0.74, 0.473, and 0.223, respectively, for the LMR model. The results indicated that the selected GEP model delivered superior performance with a higher R2value and lower errors.展开更多
The smallholder irrigation sector in Kenya is considered inadequately developed. The study views unawareness of critical success factors in the smallholder irrigation sector as contributing to poor performance of smal...The smallholder irrigation sector in Kenya is considered inadequately developed. The study views unawareness of critical success factors in the smallholder irrigation sector as contributing to poor performance of smallholder irrigation projects. Consequently, the study investigated influence of farmer capacity building in institutional linkages on performance of smallholder irrigation projects in Migori County, Kenya. The study embraced a pragmatic view of philosophy, and used cross sectional and correlation research design. The target population was 2815, and comprised farmers drawn from fifteen smallholder irrigation projects that receive water from River Kuja through Lower Kuja Project. The sample size was 341. The study used systematic random sampling procedure to draw the sample, and collected data using questionnaire. Data was analysed using descriptive and inferential statistics. The study established that farmer capacity building in institutional linkages has a significant influence on performance of smallholder irrigation projects (r = 0.803, R<sup>2</sup> = 0.645, F (5, 331) = 120.254 and p < 0.000 < 0.05). Thus, the study recommends that Migori County Government come up with policies that link smallholder irrigation projects in Lower Kuja Project to institutions that provide land ploughing services, certified seeds and fertilisers, control of crop pests and diseases, transportation of farm produce and marketing of farm produce.展开更多
<strong>Purpose: </strong>Nowadays, the worldwide economic recession has created numerous challenges in the Public Sector of Greece, which in turn affect the sustainability of public enterprises. Overall, ...<strong>Purpose: </strong>Nowadays, the worldwide economic recession has created numerous challenges in the Public Sector of Greece, which in turn affect the sustainability of public enterprises. Overall, there is a high pressure to increase productivity and reduce operating costs. The need to adapt to the new environment is pushing public organizations to implement Lean Management strategies in accordance with Private Sector standards. However, the limited budget, public deficits and debts, bureaucratic culture, political dependence and lack of transparency present several issues. These pose a serious threat to successful implementation of Lean practices in the long-run. Lack of relevant research and dichotomous role of public service organizations make this study very interesting. This research paper is aiming at exploring and highlighting the impact of the most important Critical Success Factors (CSFs) for the effective integration of Lean Management principles in Public Utility organizations in Greece by combining bibliographic research and empirical—with the quantitative method-research through case studies. <strong>Research Methodology: </strong>The research method combines bibliographic research and empirical—with the quantitative method. Quantitative method was employed on a sufficient sample of public employees from two of the largest public companies of Greece: Public Power Corporation (PPC S.A.) and Athens Water Supply and Sewerage Company (EYDAP S.A.) in order to investigate the impact of the most important CSFs on successful Lean Transformation of them. <strong>Findings:</strong> Quantitative findings from this research illustrated that the most important CSFs that have a positive impact on successful Lean Transformation on Greek public organizations/utilities are: Effective Communication, flexible Organizational Infrastructure, Customer Focus, Linking Lean to Suppliers, Business Plan and Vision, competent Change Management, Top Management Support and Commitment, Training and Education, as well as Selection of Staff. On the contrary, the existence of a bureaucratic Organizational Culture has a negative effect on successful integration of Lean Management. <strong>Limitations: </strong>Important limitations of this study are the utilization of a convenience sample and the strict focus on Greek public organizations operating in a competitive environment.展开更多
This study aimed to assess land degradation sensitivity of an area contributing to desertification risk in Lam Ta Kong Watershed using Environmental Sensitivity Area Index(ESAI).Five risk factors comprised climatic,so...This study aimed to assess land degradation sensitivity of an area contributing to desertification risk in Lam Ta Kong Watershed using Environmental Sensitivity Area Index(ESAI).Five risk factors comprised climatic,soil,geographical,land utilization and vegetation,and water resources factors together with fifteen sub-factors were used to analyze the sensitivity to land degradation.The spatial analysis was calculated using Geographic Information System(GIS)and Remote Sensing(RS)techniques.The key factors influencing land degradation risks in the watershed area were analyzed using the triangular fuzzy numbers(TFNs)method.The results showed that approximately 33%of Lam Ta Kong watershed was affected by a high desertification risk excluded the water bodies and around 24.64%of the area suffered from a moderate risk.This research pointed out that key factors causing land degradation and desertification in the watershed area were related to the soil factors,followed by climatic,geographical factors,water resources,and land utilization and vegetation,respectively.The results of this study can be used as a database for planning and implementing area-based mitigations and measures as well as for land use planning in the watershed area.展开更多
The 2004 Indian Ocean Tsunami triggered significant destruction to housing and related infrastructures across various coastal districts of south India.Research shows that tsunami reconstruction projects in Kerala expe...The 2004 Indian Ocean Tsunami triggered significant destruction to housing and related infrastructures across various coastal districts of south India.Research shows that tsunami reconstruction projects in Kerala experienced different degrees of success and failure.On this background,this study explored factors that contributed to the successful implementation of tsunami housing projects in Kerala by(1)consolidating various critical success factors(CSFs)for post-disaster reconstruction(PDR)projects under‘‘project management success traits’’through content analysis of existing literature;(2)deriving a conceptual model that envisages project success in PDR contexts;and(3)assessing the impacts of those success traits on tsunami housing projects using confirmatory factor analysis.Necessary data were gathered through a survey of various stakeholders involved in tsunami reconstruction projects in Kerala using structured questionnaires.The research revealed that PDR project success is attributed to critical dimensions of project management such as institutional mechanisms,reconstruction strategies,project implementation,and stakeholder management.A conceptual model with the interplay of project success,success traits,as well as their CSFs identified the project management actions that must be monitored during reconstruction.Since the project management approach is widely recognized for PDR projects,these success traits hold huge potential for effective organization and management of housing reconstruction projects.The study also helped to identify project management traits that need improvements for the successful implementation of post-disaster housing projects in Kerala.Thus the research findings can serve as a foundational study for formulating project management strategies appropriate to PDR projects in Kerala.展开更多
In this paper the Hong Kong-Zhuhai-Macao Bridge project is taken as a case to analyze supplier development in infrastructure mega-projects. Compared with manufacturing industry, the characteristics of supplier develop...In this paper the Hong Kong-Zhuhai-Macao Bridge project is taken as a case to analyze supplier development in infrastructure mega-projects. Compared with manufacturing industry, the characteristics of supplier development in infrastructure mega-projects is analyzed in term of development motives, supplier selection, quality management, production mode, owner participation and risks. The critical factors influencing the construction supplier development are identified, which include incentives, collaboration, future market, trust and bilateral communication. Furthermore, focusing on the incentives for the supplier's product quality and production capacity improvement, decision-making framework models are proposed to design the incentive mechanisms.展开更多
It is often argued that the core of organizational success is efficient collaboration.Some authors even posit that efficient collaboration is more important to organizational innovation and performance than individual...It is often argued that the core of organizational success is efficient collaboration.Some authors even posit that efficient collaboration is more important to organizational innovation and performance than individual skills or expertise.However,the lack of efficient models to manage collaboration properly is a major constraint for organizations to profit from internal and external collaborative initiatives.Currently,much of the collaboration in organizations occurs through virtual network channels,such as e-mail,Yammer,Jabber,Microsoft Teams,Skype,and Zoom.These are even more important in situations where different time zones and even threats of a pandemic constrain face-to-face human interactions.This work introduces a multidisciplinary heuristic model developed based on project risk management and social network analysis centrality metrics graph-theory to quantitatively measure dynamic organizational collaboration in the project environment.A case study illustrates the proposed model’s implementation and application in a real virtual project organizational context.The major benefit of applying this proposed model is that it enables organizations to quantitatively measure different collaborative,organizational,and dynamic behavioral patterns,which can later correlate with organizational outcomes.The model analyzes three collaborative project dimensions:network collaboration cohesion evolution,network collaboration degree evolution,and network team set variability evolution.This provides organizations an innovative approach to understand and manage possible collaborative project risks that may emerge as projects are delivered.Organizations can use the proposed model to identify projects’critical success factors by comparing successful and unsuccessful delivered projects’dynamic behaviors if a substantial number of both project types are analyzed.The proposed model also enables organizations to make decisions with more information regarding the support for changes in observed collaborative patterns as demonstrated by statistical models in general,and linear regressions in particular.Further,the proposed model provides organizations with a completely bias-free data-collection process that eliminates organizational downtime.Finally,applying the proposed model in organizations will reduce or eliminate the risks associated with virtual collaborative dynamics,leading to the optimized use of resources;this will transform organizations to become more lean-oriented and significantly contribute to economic,social,and environmental global sustainability.展开更多
基金supported by the Ministry of Science and Technology(MOST),Taiwan,R.O.C.(104-2410-H-327-024-).
文摘The advantages of a cloud computing service are cost advantages,availability,scalability,flexibility,reduced time to market,and dynamic access to computing resources.Enterprises can improve the successful adoption rate of cloud computing services if they understand the critical factors.Tofind critical factors,this studyfirst reviewed the literature and established a three-layer hierarch-ical factor table for adopting a cloud computing service based on the Technology-Organization-Environment framework.Then,a hybrid method that combines two multi-criteria decision-making tools—called the Fuzzy Analytic Network Process method and the concept of VlseKriterijumska Optimizacija I Kompromisno Resenje acceptable advantage—was used to objectively identify critical factors for the adop-tion of a cloud computing service,replacing the subjective decision of the authors.The results of this study determinedfive critical factors,namely data access secur-ity,information transmission security,senior management support,fallback cloud management,and employee acceptance.Finally,the paper presents thefindings and implications of the study.
文摘The aim of this paper is to present through information collected via qualitative analysis in order to provide an alternative perspective to classify critical factors and their correlations in the processes of degradation of river basins in countries in development in an ordered way.This study was started with a bibliographical review for gathering relevant information about the main factors,which was submitted to specialists and related professionals via survey developed in a format of answers on Likert scale,with the analyses of data from the respondents as well as their contribution within sample assembly exploratory factorial analysis and the charge factor item from the questionnaire with usage of polychoric correlation matrix with which it is proposed to establish the ordering of the factors relevance as well as their correlations through parametric statistical analysis with the usage of a generalized model of partial credit which belongs to the family of the models for polyatomic gradual answers to the item response theory(IRT)and the applying of cluster analysis(ICLUST)with the usage of both alpha and omega coefficient for the estimation of the variables group,with the R tool.As a result,the present study aims to establish a comprehension of the main factors for the ordering of the actions and attention of public and private sectors towards the preservation of urban river basins.
基金supported by Consejo Nacional de Investigaciones Científica y Técnicas,Agencia Nacional de Promociòn Científica y Tecnològica,Universidad Nacional de Cuyo,and Organization for the Prohibition of Chemical Weapons.
文摘Certain wild animals represent sentinels to address issues related to environmental pollution,since they can provide integrative data on both pollutant exposure and biological effects.Despite their technological benefits,PBDEs are considered a threat to environmental health due to their persistence,toxicity,and capacity to be accumulated.These pollutants have been found geographically widespread in fish,particularly in predator species such as trout.The aim of this work is to critically review the applicability and usefulness of wild trout for assessing PBDEs in freshwater environments.Reviewed reports include data from highly industrialized areas as well as areas from remote regions with relatively low human activity,including European and North American great lakes and freshwater environments in Europe,Greenland,subarctic areas and Patagonia,respectively.A summary of relevant factors were grouped into organism-specific factors(food habits,age,size,lipid content,sex and reproduction,tissue type,mechanism of contaminant uptake and metabolism),and PBDE levels in the surrounding environment(sediment).Five wild trout species[rainbow trout(Oncorhynchus mykiss),brown trout(Salmo trutta),lake trout(Salvelinus namaycush),arctic char(Salvelinus alpinus),and brook trout(Salvelinus fontinalis)],collected worldwide within the 1994 to present time frame,were considered.Multivariate techniques(principal component analysis-PCA)and mapping approach,showed clear differences in geographic distribution patterns of PBDE levels in trout depending on the region studied:wild trout from European and North American great lakes have the highest PBDE loads.This pattern could be due to high industrial activity at these locations.A correlational approach used to explore intraspecific relationships between PBDE levels and morphometry,showed positive relationships only for brown trout.Further,brown trout showed the highest trout-to-sediment ratios,which is suggestive of a relatively greater capacity of this species to accumulate PBDEs in relation to sediment levels.Overall,results suggest that adult wild trout could be useful as a PBDE bioindicator.
基金Supported by Anna University,Chennai for the funding done under DST PURSE Ⅱ–Junior Research Fellowship 9500/PD2/2014,Dated24.03.2015
文摘Manufacturing industries are facing challenges in the implementation of agile manufacturing in their products and processes.Agility is widely accepted as a new competitive concept in the manufacturing sector in fulfilling varying customer demand. Thus,evaluation of agile manufacturing in industries has become a necessity. The success of an organisation depends on its ability to manage finding the critical success factors and give them special and continued attention in order to bring about high performance. This paper proposes a set of critical success factors(CSFs) for evaluating agile manufacturing considered appropriate for the manufacturing sector.The analytical hierarchy process(AHP) method is applied for prioritizing the success factors, by summarizing the opinions of experts. It is believed that the proposed CSFs enable and assist manufacturing industries to achieve a higher performance in agile manufacturing so as to increase competitiveness.
文摘In improving the competitiveness of business organi sa tion in the 21st century, minimising cost and increasing productivity are no lon ger factors that could promise the success. The changes in customer trends whic h focusing more on product or service customising, high quality and short delive ry times are additional crucial factors that organisation should be aware of. T hese factors have direct relations on how the management could utilise the capab ility of its supply chain management (SCM). The importance of SCM in organisati on specifically to manufacturer is to play a vital role in managing the flow of material and information along the chain from suppliers to customers. In a trad itional way, SCM is mainly manage by the production department in organisation b ut with the advancement in information technology, resulted the changes in worki ng environment. One of the ways that could be implemented in decision making p rocess in order to improve the effectiveness and efficiency of the decision is t hrough collaborative environment. Due to this situation, there is a need to rede sign the existing SCM in order to optimise its capability and functionality in t he way to ensure the organisation competitiveness is sustainable. A minor or ma jor alignment to SCM business processes should be done in order to streamline th e flow of information, which could also affect the flow of materials. Factors s uch as SCM operational, structural and even its managerial are among the issues that are critical in redesigning its business process. Each of these factors has its own attributes such as lead-times, complexity, frequency and organisationa l setting that could lead in improving organisational competitiveness. In additi on, by identifying these factors, it would help the management to plan and desig n the collaborative SCM that would effectively correspond to the changes in busi ness and customer trends. The intention of the paper is to promote a list of fa ctors and attributes, which are critical in redesigning an existing SCM in order to shift its environment to become collaborative SCM. By utilising these facto rs and attributes, a model for redesigning SCM into collaborative environment is currently developed by the author and will be used in the next stage of his res earch.
文摘The purpose of this paper is to provide a structured literature review of cross-border e-logistics research,uncover existing gaps and opportunities,try to find practical strategies to balance logistics costs and service levels,and improve logistics efficiency and customer satisfaction for future cross-border e-logistics research.Meanwhile this paper also uses the real data to test the tradeoff between transportation and warehousing cost.In addition,regression empirical analysis is used to make up for the lack of empirical drawbacks of many articles in the field and the result can be instructive and referential for cross-border e-commerce enterprises to make decisions on weighing logistics cost and service level to improve logistics efficiency.
基金supported by National Natural Science Foundation of China(Grant Nos.51938008 and 52090084).
文摘The development of urban underground space(UUS)is of great significance for sustainable urban development because it has potential to solve many urban problems.However,the development of UUS is limited because there are still a lot of constraints and challenges.To better understand the constraining factors of developing UUS and improve the development and utilization of UUS,this study conducts a comprehensive survey of existing literature retrieved from the Web of Science Core Collection database.Five main constraining factors,including the limited geological conditions,high cost,lack of natural light and ventilation,high incidence,and difficulty in collecting data and information on UUS,have been discussed to better understand how they affect the development of UUS.Based on the survey,the critical success factors of developing UUS,such as the effective governance structure,planning system for integrating UUS into urban development,coordination of the design of ground and underground,delineation of land property rights of UUS,and application of information techniques in the use of UUS,have been identified and discussed.In addition,knowledge gaps in the studies on development of UUS have been identified.Finally,the research trends and future directions have been proposed for better understanding and practice of UUS development.
文摘The tension cracks and joints in rock or soil slopes affect their failure stability.Prediction of rock or soil slope failure is one of the most challenging tasks in the earth sciences.The actual slopes consist of inhomogeneous materials,complex morphology,and erratic joints.Most studies concerning the failure of rock slopes primarily focused on determining Factor of Safety(FoS)and Critical Slip Surface(CSS).In this article,the effect of inclined tension crack on a rock slope failure is studied numerically with Shear Strength Reduction Factor(SRF)method.An inclined Tension Crack(TC)influences the magnitude and location of the rock slope’s Critical Shear Strength Reduction Factor(CSRF).Certainly,inclined cracks are more prone to cause the failure of the slope than the vertical TC.Yet,all tension cracks do not lead to failure of the slope mass.The effect of the crest distance of the tension crack is also investigated.The numerical results do not show any significant change in the magnitude of CSRF unless the tip of the TC is very near to the crest of the slope.ATC is also replaced with a joint,and the results differ from the corresponding TC.These results are discussed regarding shear stress and Critical Slip Surface(CSS).
基金This work was supported/funded by the Ministry of Higher Education/University of Technology Malaysia under the Fundamental Research Grant Scheme(FRGS/1/2019/TK08/UTM/02/4).
文摘Industry 4.0 is expected to play a crucial role in improving energy management and personnel performance in power plants.Poor performance problem in maintaining power plants is the result of both human errors,human factors and the poor implementation of automation in energy management.This problem can potentially be solved using artificial intelligence(AI)and an integrated management system(IMS).This article investigates the current challenges to improving personnel and energy management performance in power plants,identifies the critical success factors(CSFs)for an integrated intelligent framework,and develops an intelligent framework that enables power plants to improve performance.The theoretical basis is founded on a systematic literature review to locate 110 out of 3108 papers studied carefully to examine the performance architecture that best enables effective maintenance.The findings from this literature review are combined with expert judgment and the big data advantages of AI applications to develop an intelligent model.Data are collected from a power plant in Iraq.To ensure the reliability of the proposed model,various hypotheses are tested using structural equation modeling.The results confirm that the measurement model is acceptable,and that the hypotheses are supported and significant.A case study demonstrates the strong relationship and significance between big data of performance and the CSFs.It is hoped that this model will be adopted to enable performance improvement in power plants.
文摘Prediction of mode I fracture toughness(KIC) of rock is of significant importance in rock engineering analyses. In this study, linear multiple regression(LMR) and gene expression programming(GEP)methods were used to provide a reliable relationship to determine mode I fracture toughness of rock. The presented model was developed based on 60 datasets taken from the previous literature. To predict fracture parameters, three mechanical parameters of rock mass including uniaxial compressive strength(UCS), Brazilian tensile strength(BTS), and elastic modulus(E) have been selected as the input parameters. A cluster of data was collected and divided into two random groups of training and testing datasets.Then, different statistical linear and artificial intelligence based nonlinear analyses were conducted on the training data to provide a reliable prediction model of KIC. These two predictive methods were then evaluated based on the testing data. To evaluate the efficiency of the proposed models for predicting the mode I fracture toughness of rock, various statistical indices including coefficient of determination(R2),root mean square error(RMSE), and mean absolute error(MAE) were utilized herein. In the case of testing datasets, the values of R2, RMSE, and MAE for the GEP model were 0.87, 0.188, and 0.156,respectively, while they were 0.74, 0.473, and 0.223, respectively, for the LMR model. The results indicated that the selected GEP model delivered superior performance with a higher R2value and lower errors.
文摘The smallholder irrigation sector in Kenya is considered inadequately developed. The study views unawareness of critical success factors in the smallholder irrigation sector as contributing to poor performance of smallholder irrigation projects. Consequently, the study investigated influence of farmer capacity building in institutional linkages on performance of smallholder irrigation projects in Migori County, Kenya. The study embraced a pragmatic view of philosophy, and used cross sectional and correlation research design. The target population was 2815, and comprised farmers drawn from fifteen smallholder irrigation projects that receive water from River Kuja through Lower Kuja Project. The sample size was 341. The study used systematic random sampling procedure to draw the sample, and collected data using questionnaire. Data was analysed using descriptive and inferential statistics. The study established that farmer capacity building in institutional linkages has a significant influence on performance of smallholder irrigation projects (r = 0.803, R<sup>2</sup> = 0.645, F (5, 331) = 120.254 and p < 0.000 < 0.05). Thus, the study recommends that Migori County Government come up with policies that link smallholder irrigation projects in Lower Kuja Project to institutions that provide land ploughing services, certified seeds and fertilisers, control of crop pests and diseases, transportation of farm produce and marketing of farm produce.
文摘<strong>Purpose: </strong>Nowadays, the worldwide economic recession has created numerous challenges in the Public Sector of Greece, which in turn affect the sustainability of public enterprises. Overall, there is a high pressure to increase productivity and reduce operating costs. The need to adapt to the new environment is pushing public organizations to implement Lean Management strategies in accordance with Private Sector standards. However, the limited budget, public deficits and debts, bureaucratic culture, political dependence and lack of transparency present several issues. These pose a serious threat to successful implementation of Lean practices in the long-run. Lack of relevant research and dichotomous role of public service organizations make this study very interesting. This research paper is aiming at exploring and highlighting the impact of the most important Critical Success Factors (CSFs) for the effective integration of Lean Management principles in Public Utility organizations in Greece by combining bibliographic research and empirical—with the quantitative method-research through case studies. <strong>Research Methodology: </strong>The research method combines bibliographic research and empirical—with the quantitative method. Quantitative method was employed on a sufficient sample of public employees from two of the largest public companies of Greece: Public Power Corporation (PPC S.A.) and Athens Water Supply and Sewerage Company (EYDAP S.A.) in order to investigate the impact of the most important CSFs on successful Lean Transformation of them. <strong>Findings:</strong> Quantitative findings from this research illustrated that the most important CSFs that have a positive impact on successful Lean Transformation on Greek public organizations/utilities are: Effective Communication, flexible Organizational Infrastructure, Customer Focus, Linking Lean to Suppliers, Business Plan and Vision, competent Change Management, Top Management Support and Commitment, Training and Education, as well as Selection of Staff. On the contrary, the existence of a bureaucratic Organizational Culture has a negative effect on successful integration of Lean Management. <strong>Limitations: </strong>Important limitations of this study are the utilization of a convenience sample and the strict focus on Greek public organizations operating in a competitive environment.
基金This research is funded by the“Innovation in Increasing the Organic Carbon in Soil for Sustainable Agricultural Purpose in Saline Soil Areas:First Year Pilot Project at the Lam Ta Kong Watershed”,Ratchadaphisek Somphot Endowment Fund 2014,Chulalongkorn University(CU-57-090-IC).
文摘This study aimed to assess land degradation sensitivity of an area contributing to desertification risk in Lam Ta Kong Watershed using Environmental Sensitivity Area Index(ESAI).Five risk factors comprised climatic,soil,geographical,land utilization and vegetation,and water resources factors together with fifteen sub-factors were used to analyze the sensitivity to land degradation.The spatial analysis was calculated using Geographic Information System(GIS)and Remote Sensing(RS)techniques.The key factors influencing land degradation risks in the watershed area were analyzed using the triangular fuzzy numbers(TFNs)method.The results showed that approximately 33%of Lam Ta Kong watershed was affected by a high desertification risk excluded the water bodies and around 24.64%of the area suffered from a moderate risk.This research pointed out that key factors causing land degradation and desertification in the watershed area were related to the soil factors,followed by climatic,geographical factors,water resources,and land utilization and vegetation,respectively.The results of this study can be used as a database for planning and implementing area-based mitigations and measures as well as for land use planning in the watershed area.
文摘The 2004 Indian Ocean Tsunami triggered significant destruction to housing and related infrastructures across various coastal districts of south India.Research shows that tsunami reconstruction projects in Kerala experienced different degrees of success and failure.On this background,this study explored factors that contributed to the successful implementation of tsunami housing projects in Kerala by(1)consolidating various critical success factors(CSFs)for post-disaster reconstruction(PDR)projects under‘‘project management success traits’’through content analysis of existing literature;(2)deriving a conceptual model that envisages project success in PDR contexts;and(3)assessing the impacts of those success traits on tsunami housing projects using confirmatory factor analysis.Necessary data were gathered through a survey of various stakeholders involved in tsunami reconstruction projects in Kerala using structured questionnaires.The research revealed that PDR project success is attributed to critical dimensions of project management such as institutional mechanisms,reconstruction strategies,project implementation,and stakeholder management.A conceptual model with the interplay of project success,success traits,as well as their CSFs identified the project management actions that must be monitored during reconstruction.Since the project management approach is widely recognized for PDR projects,these success traits hold huge potential for effective organization and management of housing reconstruction projects.The study also helped to identify project management traits that need improvements for the successful implementation of post-disaster housing projects in Kerala.Thus the research findings can serve as a foundational study for formulating project management strategies appropriate to PDR projects in Kerala.
基金funded by the National Natural Science Foundation of China(Grant No.71390524)
文摘In this paper the Hong Kong-Zhuhai-Macao Bridge project is taken as a case to analyze supplier development in infrastructure mega-projects. Compared with manufacturing industry, the characteristics of supplier development in infrastructure mega-projects is analyzed in term of development motives, supplier selection, quality management, production mode, owner participation and risks. The critical factors influencing the construction supplier development are identified, which include incentives, collaboration, future market, trust and bilateral communication. Furthermore, focusing on the incentives for the supplier's product quality and production capacity improvement, decision-making framework models are proposed to design the incentive mechanisms.
文摘It is often argued that the core of organizational success is efficient collaboration.Some authors even posit that efficient collaboration is more important to organizational innovation and performance than individual skills or expertise.However,the lack of efficient models to manage collaboration properly is a major constraint for organizations to profit from internal and external collaborative initiatives.Currently,much of the collaboration in organizations occurs through virtual network channels,such as e-mail,Yammer,Jabber,Microsoft Teams,Skype,and Zoom.These are even more important in situations where different time zones and even threats of a pandemic constrain face-to-face human interactions.This work introduces a multidisciplinary heuristic model developed based on project risk management and social network analysis centrality metrics graph-theory to quantitatively measure dynamic organizational collaboration in the project environment.A case study illustrates the proposed model’s implementation and application in a real virtual project organizational context.The major benefit of applying this proposed model is that it enables organizations to quantitatively measure different collaborative,organizational,and dynamic behavioral patterns,which can later correlate with organizational outcomes.The model analyzes three collaborative project dimensions:network collaboration cohesion evolution,network collaboration degree evolution,and network team set variability evolution.This provides organizations an innovative approach to understand and manage possible collaborative project risks that may emerge as projects are delivered.Organizations can use the proposed model to identify projects’critical success factors by comparing successful and unsuccessful delivered projects’dynamic behaviors if a substantial number of both project types are analyzed.The proposed model also enables organizations to make decisions with more information regarding the support for changes in observed collaborative patterns as demonstrated by statistical models in general,and linear regressions in particular.Further,the proposed model provides organizations with a completely bias-free data-collection process that eliminates organizational downtime.Finally,applying the proposed model in organizations will reduce or eliminate the risks associated with virtual collaborative dynamics,leading to the optimized use of resources;this will transform organizations to become more lean-oriented and significantly contribute to economic,social,and environmental global sustainability.
