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| 1 | Artificial intelligence:a survey on evolution,models,applications and future trends显示文摘Artificial intelligence(AI)is one of the core drivers of industrial development and a critical factor in promoting the integration of emerging technologies,such as graphic processing unit,Internet of Things,cloud computing,and the blockchain,in the new generation of big data and Industry 4.0.In this paper,we construct an extensive survey over the period 1961-2018 of AI and deep learning.The research provides a valuable reference for researchers and practitioners through the multi-angle systematic analysis of AI,from underlying mechanisms to practical applications,from fundamental algorithms to industrial achievements,from current status to future trends.Although there exist many issues toward AI,it is undoubtful that AI has become an innovative and revolutionary assistant in a wide range of applications and fields. | Yang Lu | 2019 | Journal of Management Analytics2019，6，1： | 14 |
| 2 | How technological proximity affect collaborative innovation?An empirical study of China’s Beijing-Tianjin-Hebei region显示文摘Based on joint-innovation patent data from 2000 to 2016 in the Beijing-Tianjin-Hebei region of China,the purpose of this paper is to analyze how technological proximity affects university-industry collaborative innovation in the Beijing-Tianjin-Hebei region.We adopt a 1:1 matching design to conduct an empirical study.The results show that the effect of technological proximity on the formation of collaborative innovation displays an inverted U-shape,and geographical proximity and institutional proximity play a positive role of forming a tie.Geographical proximity and institutional proximity as a coordination mechanism,have negatively influenced the relationship between technological proximity and the formation of university-industry collaborative innovation.Furthermore,university strength improves the possibility of collaborative innovation.These findings contributed to the understanding of the relationship between technological proximity and collaborative innovation. | Hongjun Chen Fuji Xie | 2018 | Journal of Management Analytics2018，5，4： | 9 |
| 3 | Blockchain and the related issues:a review of current research topics显示文摘The blockchain represents emerging technologies and future trends.For the traditional social organization and mode of operation,the development of the blockchain is a revolution.As a decentralized infrastructure and distributed general ledger agreement,the blockchain presents us with a great opportunity to establish data security and trust for automation and intelligence development in the Internet of Things(IoT)and it creates a new un-centralized programmable smart ecosystem.Our research synthesizes and analyses extant articles that focus on blockchain-related perspectives which will potentially play an important role in sustainable development in the world.Blockchain applications and future directions always attract more attention.Blockchain technology provides strong scalability and interoperability between the intelligent and the physical worlds. | Yang Lu | 2018 | Journal of Management Analytics2018，5，4： | 8 |
| 4 | Optimal quality level,order quantity and selling price for the retailer in a two-level supply chain显示文摘For a classical order quantity/pricing problem,we present a geometric programming(GP)approach to find the optimal selling price,order quantity and quality level to maximize the profit for the retail firm.Traditional models such as EOQ are not able to handle the nonlinearity of costs and demand.We adopt the GP approach and make a proper transformation of the model so as to solve this classical problem and obtain the global optimal solution.In addition to the optimal solutions,we also perform a sensitivity analysis.The study shows once more that GP is an excellent approach when decision variables interact in a nonlinear,especially exponential manner. | Sihua Zhou Guohua Wan Pengzhu Zhang Yuan Li | 2014 | Journal of Management Analytics2014，1，3： | 6 |
| 5 | An EPQ model with variable production,probabilistic deterioration and partial backlogging under inflation显示文摘This paper develops an economic production quantity(EPQ)model under the effect of inflation and time value of money.The rate of replenishment is considered to be a variable and the generalized unit production cost function is formulated by incorporating several factors,such as raw material,labour,replenishment rate,advertisements and other factors of the manufacturing system.The selling price of a unit is determined by a mark-up over the production cost.We have considered three types of continuous probabilistic deterioration function,and also considered that the holding cost of the item per unit time is assumed to be an increasing linear function of time spent in storage.In addition,shortages are allowed and partially backlogged.This model aids in minimizing the total inventory cost by finding the optimal cycle length and the optimal production quantity.The optimal solution of the model is illustrated with the help of numerical examples. | M.Palanivel R.Uthayakumar | 2014 | Journal of Management Analytics2014，1，3： | 6 |
| 6 | Healthcare data analytics:using a metadata annotation approach for integrating electronic hospital records显示文摘The data in electronic medical records(EMR)are complex in structure.They are independent,yet related to each other.In order to improve information access through the use of EMR,annotating work on these data is necessary.The annotation on metadata,the resource data which contain a meta-model of the database,is the basis of the annotating work if a semi-automated or an automated annotating approach which aims at making the database more accessible is expected.In this study,a method has been proposed to transform the terms which cannot be matched directly by changing them literally but maintaining their semantics,and then annotating them indirectly.After the transforming work,a refinement method which is reducible to phrase sense disambiguation(PSD)is employed to ensure accuracy.A pilot study on a hospital database has been conducted to test the accuracy and effectiveness of the proposed method. | Boyi Xu Ke Xu LiuLiu Fu Ling Li Weiwei Xin Hongming Cai | 2016 | Journal of Management Analytics2016，3，2： | 6 |
| 7 | Big data analytics and business analytics显示文摘Over the past few decades,with the development of automatic identification,data capture and storage technologies,people generate data much faster and collect data much bigger than ever before in business,science,engineering,education and other areas.Big data has emerged as an important area of study for both practitioners and researchers.It has huge impacts on data-related problems.In this paper,we identify the key issues related to big data analytics and then investigate its applications specifically related to business problems. | Lian Duan Ye Xiong | 2015 | Journal of Management Analytics2015，2，1： | 5 |
| 8 | Multi-item EPQ model with learning effect on imperfect production over fuzzy-random planning horizon显示文摘Uncertainty is certain in the world of uncertainty.This study revisits an economic production quantity(EPQ)model with shortages for stock-dependent demand of the items with reworking and disposing of the imperfect ones over a random planning horizon under the joint effect of inflation and time value of money,where the expected time length is imprecise in nature.Transmission of learning effect has been incorporated to reduce the defective production.The total expected profit over the random planning horizon is maximized subject to the imprecise space constraint.The possibility,necessity and credibility measures have been introduced to defuzzify the model.The simulation-based genetic algorithm is used to make decision for the above EPQ model in different measures of uncertainty.The model is illustrated through an example.Sensitivity analysis shows the impacts of different parameters on the objective function in the model. | Amalesh Kumar Manna Barun Das Jayanta Kumar Dey Shyamal Kumar Mondal | 2017 | Journal of Management Analytics2017，4，1： | 5 |
| 9 | Big data analytics with applications显示文摘In this paper,recent developments on the Internet of Things(IoT)and its applications are surveyed,and the impact of newly developed Big Data(BD)on manufacturing information systems is especially discussed.Big Data analytics(BDA)has been identified as a critical technology to support data acquisition,storage,and analytics in data management systems in modern manufacturing.The purpose of the presented work is to clarify the requirements of predictive systems,and to identify research challenges and opportunities on BDA to support cloudbased information systems. | Zhuming Bi David Cochran | 2014 | Journal of Management Analytics2014，1，4： | 5 |
| 10 | An inventory model with finite replenishment,probabilistic deterioration and permissible delay in payments显示文摘This paper develops an inventory model for deteriorating items with finite replenishment rate under a progressive payment scheme within the cycle time.In this model,the deterioration function follows a probability distribution such as a(1)uniform distribution,(2)triangular distribution or(3)beta distribution.Here,the retailer is allowed a trade-credit offer by the supplier to buy more items.This model aids in minimizing the total inventory cost of the retailer by finding the optimal cycle length,the optimal time length of replenishment and the optimal order quantity.Some theorems have been framed to characterize the optimal solutions.The necessary and sufficient conditions of the existence and uniqueness of the optimal solutions are also provided.The optimal solution of the model is illustrated with the help of numerical examples,and numerical comparisons between the three models are also given.Finally,sensitivity analysis and graphical representations are given to demonstrate the model. | M.Palanivel S.Priyan R.Uthayakumar | 2015 | Journal of Management Analytics2015，2，3： | 5 |
| 11 | A comprehensive review from sequential association computing to Hadoop-MapReduce parallel computing in a retail scenario显示文摘Today,the customer’s requirements are entirely transformed.Many big retail organizations are facing sudden decline in the sales and revenues caused due to indecisive and erratic purchasing habits of recent generation of users,as they get abundant preferred information such as cheaper rates,amazing offers,discounts,comparison of similar products,etc.over their smartphones or laptops hence they straightaway place order instead of walking down to showroom.As a result,large companies such as Tesco,Wal-Mart,Target,etc.have realized that it is requisite to shake hands with startup firms which already supports platform to retain customers either via deep exploration of transactional data or by offering lucrative offers in the benefit of customer and to promote market basket.The data which are generated from consumer purchase pattern,Big Data is a concern for companies as a result various big retail organizations are applying advanced and scalable data mining algorithms to precisely store and evaluate data in real-time manner to boost market basket analysis.This research work discusses various improved association rule mining(ARM)algorithms.The objective of this study is to identify gaps,providing opportunities for new research,to recognize expansion of Big Data analytics with retail environment and its future directions.This paper assimilates various aspects of parallel ARM algorithm for market basket analysis against sequential and distributed nature which are further escalated to Hadoop and MapReduce computing platform.Further various use cases highlighting the need of‘Big Data Retail Analytics’are discussed for emerging trends to promote sales and revenues,to keep check on competitor’s websites,comparison of various brands,enticing new customers. | Neha Verma Jatinder Singh | 2017 | Journal of Management Analytics2017，4，4： | 4 |
| 12 | Evaluating the environmental efficiency of the U.S.airline industry using a directional distance function DEA approach显示文摘This study applies a directional distance function(DDF)data envelopment analysis(DEA)model to measure the environmental efficiency of 12 U.S.airlines 2013–2016 by considering flight delay and greenhouse gas(GHG)emissions as joint undesirable outputs.First,the environmental efficiency of airlines is compared using the CCR DEA(without flight delay)and DDF DEA(with flight delay).We find that several airlines experienced substantial changes in environmental efficiency scores when flight delay is considered.Secondly,a tobit regression is used to explore whether the environmental factors of fleet age,ownership type,freight traffic,market share,and carrier type affect airlines’environmental efficiency.The results demonstrate that all of these factors significantly influence airline performance. | Yuan Xu Yong Shin Park Ju Dong Park Wonjoo Cho | 2021 | Journal of Management Analytics2021，8，1： | 4 |
| 13 | An inventory model under development cost-dependent imperfect production and reliability-dependent demand显示文摘This paper considers a model that deals with an imperfect production process where both perfect and imperfect quality items are produced.Here,demand depends on selling price and reliability of the product.Each manufacturing company expects to produce perfect quality items.But due to the long-run process,several kinds of problem such as labor,machinery,and technology arise.As a result,the manufacturing system becomes out-of-control state and consequently produces both perfect and imperfect quality items.Perfect items are ready to sell but imperfect items are reworked at a cost to become perfect.Reworking cost,reliability of the product and reliability parameter of the manufacturing system can be improved by introducing the development cost and also by improving the quality of the raw material of the production system.Under such circumstances,a profit function has been developed to find the optimum values of reliability parameter of the manufacturing system,reliability of the product and duration of production such that a manufacturer gets a maximum profit.Finally,the model has been illustrated with some numerical examples exploring the sensitivity analysis with respect to some parameters. | Barun Khara Jayanta Kumar Dey Shyamal Kumar Mondal | 2017 | Journal of Management Analytics2017，4，3： | 4 |
| 14 | Two-echelon production-inventory system with fuzzy production rate and promotional effort dependent demand显示文摘Intelligent manufacturing design of a complex production-inventory system becomes a key issue for the organization of responsiveness to uncertainties.This paper addresses a two-echelon production-inventory model for a non-repairable product where the system consists of single manufacturer and single retailer.The manufacturer procures raw material(which also contains imperfect raw materials)from an outside supplier then proceeds to convert perfect-quality raw material as a finished product,and finally delivers to the retailer.In this study we assume that the demand is sensitive to promotional efforts/sales teams’initiatives and the production rate is uncertain but possible to describe with a triangular fuzzy number.Then we use the signed distance method to defuzzify the fuzzy joint total cost and an analytical method is employed to achieve the optimal solutions so that the total costs of both manufacturer and retailer are minimized.An efficient algorithm is developed to design an intelligent manufacturing strategy such as optimal production lot-size,backlogging and the initiatives of sales teams.A numerical example and sensitivity analysis are given to demonstrate the application of the proposed model. | S.Priyan M.Palanivel R.Uthayakumar | 2015 | Journal of Management Analytics2015，2，1： | 4 |
| 15 | Selection of logistics distribution center location for SDN enterprises显示文摘The location selection of the logistics distribution center for a supply and demand network(SDN)enterprises directly affected the efficiency of the logistics system operation and the customer service level.In this paper,we present a location selection model of the logistics distribution center for SDN enterprises.In order to improve the optimization effectiveness of the traditional methods in solving the location selection problem,an improved firefly algorithm was presented.By introducing a coordination factor,the search step can be automatically adjusted,and the accuracy of the algorithm can be improved.By introducing a chaotic search strategy,the diversity of firefly populations and the global optimization ability of the algorithm can be improved.The simulation experiments showed that the improved firefly algorithm achieved a more favorable effectiveness than three other algorithms we tested. | Wei Hu Ye Hou Longwei Tian Yuan Li | 2015 | Journal of Management Analytics2015，2，3： | 4 |
| 16 | Business challenges and research directions of management analytics in the big data era显示文摘Big data analytics have been embraced as a disruptive technology that will reshape business intelligence,particularly marketing intelligence,which has have traditionally relied on market surveys to understand consumer behavior and product design.In this paper,we investigate how big data analytics will affect the landscape of business intelligence,leading to big data intelligence.Rooted in the recent literature,we delineate business opportunities and managerial challenges brought forward by the emergence of big data analytics and outline a number of research directions in big data intelligence for business. | J.Leon Zhao Shaokun Fan Daning Hu | 2014 | Journal of Management Analytics2014，1，3： | 4 |
| 17 | Multi-item fuzzy inventory model for deteriorating items in multi-outlet under single management显示文摘Multi-item inventory model with stock-dependent demand is developed in fuzzy environment.Items are deteriorated in constant rate and are sold from different outlets in the city under single management.Due to the impreciseness of different parameters,objectives as well as constraints are imprecise in nature.As optimization of fuzzy objectives as well as fuzzy constraints are not well defined,the model is formulated as a multi-objective chance constrained programming problem where optimistic/pessimistic return of the objectives with some degree of possibility/necessity are optimized and constraints are satisfied with some degree of necessity.The model is solved via Multi-Objective Genetic Algorithm(MOGA)when crisp equivalent of the problem is available.In other cases,fuzzy simulation process is proposed to check the constraints as well as to determine the optimistic/pessimistic return of the objectives.The model is illustrated with some numerical examples. | Ajoy Kumar Maiti | 2020 | Journal of Management Analytics2020，7，1： | 4 |
| 18 | What impact entrepreneurial intention?Cultural,environmental,and educational factors显示文摘Entrepreneurial intention is a key part of entrepreneurship.This paper aims to explore internal and external impact factors on entrepreneurial intention from the perspective of information transfer.It examines how cultural differences,environmental factors,and environmental education affect entrepreneurial intention.A questionnaire-based survey on Chinese and American college students is conducted to verify three hypotheses.The results show that there is no significant difference in entrepreneurial intention level between college students in China and America(American-born Chinese)college students,that individuals’perceived environmental support is positively related to their entrepreneurial intention,and that individuals’entrepreneurial education level is not positively related to their entrepreneurial intention. | Jiayue Ao Zhao Liu | 2014 | Journal of Management Analytics2014，1，3： | 4 |
| 19 | Two-warehouse inventory model for deteriorating items with demand influenced by innovation criterion in growing technology market显示文摘One of the major concerns for the technology market is the demand volatility andits impact on inventory policies. Demand volatility in the technology sector mayarise due to many factors namely customer choices, competition, growingmarket size, and so on. Often companies use rented warehouses to absorb anyfluctuations in demand. Unfortunately, warehouse and inventory researchesignore the phenomenon of growing market size to formulate policy decisions. Inthis paper, we proposed a two-warehouse inventory model with deterioration fortechnology products with linearly increasing market size where demand followsinnovation diffusion criterion. The model is based on the assumption that theholding costs in the rented warehouse are more than the own warehouse. Asimple solution procedure also discussed to solve nonlinear cost function.Numerical example and sensitivity analysis are also used to describe the utilityof the model. | Alok Kumar Udayan Chandab | 2018 | Journal of Management Analytics2018，5，3： | 3 |
| 20 | Support vector machine and ROC curves for modeling of aircraft fuel consumption显示文摘To estimate the fuel consumption of a civil aircraft,we propose to use the receiver operating characteristic(ROC)curve to optimize a support vector machine(SVM)model.The new method and procedure has been developed to build,train,validate,and apply an SVM model.A conceptual support vector network is proposed to model fuel consumption,and the flight data collected from routes are used as the inputs to train an SVM model.During the training phase,an ROC curve is defined to evaluate the performance of the model.To validate the applicability of the trained model,a case study is developed to compare the data from an aircraft performance manual and from the implemented simulation model.The investigated aircraft in the case study is a Boeing 737-800 powered by CFM-56 engines.The comparison has shown that the trained SVM model from the proposed procedure is capable of representing a complex fuel consumption function accurately for all phases during the flight.The proposed methodology is generic,and can be extended to reliably model the fuel consumption of other types of aircraft,such as piston engine aircraft or turboprop engine aircraft. | Xuhui Wang Xinfeng Chen Zhuming Bi | 2015 | Journal of Management Analytics2015，2，1： | 3 |
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