Management Support Systems and Decision-Making - …：管理与决策支持系统—…
信息系统的组成英语作文
信息系统的组成英语作文标题，The Composition of Information Systems。
Information systems play a crucial role in the modern world, serving as the backbone of countless organizations, businesses, and institutions. Understanding the components of information systems is essential for comprehending their functionality and significance. In this essay, we will delve into the various components of information systems, their functions, and their importance in today's digital age.At its core, an information system comprises hardware, software, data, people, and processes. Each component contributes uniquely to the system's overall functionality and effectiveness.Firstly, hardware refers to the physical components of the information system, including computers, servers, networking devices, and storage devices. These hardwarecomponents provide the infrastructure necessary for processing, storing, and transmitting data and information within the system.Secondly, software encompasses the programs and applications that run on the hardware. This includes operating systems, database management systems, enterprise resource planning (ERP) software, customer relationship management (CRM) software, and various other applications tailored to specific organizational needs. Software enables users to interact with the hardware, manipulate data, and perform tasks efficiently.Thirdly, data is the lifeblood of an information system. It refers to the raw facts, figures, and observations that are collected, stored, processed, and analyzed by the system. Data can take various forms, including text, numbers, images, audio, and video. Effectively managing and utilizing data is critical for decision-making, problem-solving, and achieving organizational objectives.Fourthly, people are an indispensable component ofinformation systems. Users, stakeholders, IT professionals, and other personnel play vital roles in designing, implementing, maintaining, and using information systems effectively. Human resources are responsible for defining requirements, configuring systems, troubleshooting issues, and ensuring security and compliance.Lastly, processes refer to the procedures, workflows, and methodologies employed within the information system to accomplish tasks and achieve goals. Processes encompass everything from data entry and retrieval to system maintenance and security protocols. Efficient processes streamline operations, minimize errors, and enhance productivity within the organization.The integration of these components results in a cohesive and functional information system that supports the operations and objectives of an organization. Information systems facilitate various functions, including data collection, storage, processing, analysis, dissemination, and decision-making.One of the primary functions of information systems is to support decision-making processes at all levels of an organization. Decision support systems (DSS) provide executives, managers, and other stakeholders with timely and relevant information to make informed decisions. These systems analyze data, generate reports, and present insights to facilitate strategic planning, resource allocation, and performance evaluation.Furthermore, information systems enable organizations to streamline their operations and enhance efficiency. Enterprise resource planning (ERP) systems integrate various business processes, such as finance, human resources, supply chain management, and customer relationship management, into a single, unified platform. By automating routine tasks, optimizing workflows, and facilitating communication and collaboration, ERP systems help organizations improve productivity, reduce costs, and maintain competitiveness in the marketplace.Additionally, information systems play a crucial role in facilitating communication and collaboration bothinternally and externally. Collaboration tools, such as email, instant messaging, video conferencing, and collaborative workspaces, enable employees to communicate, share ideas, and collaborate on projects in real-time, regardless of their geographical location. This enhances teamwork, fosters innovation, and accelerates decision-making processes within the organization.Moreover, information systems contribute to the strategic positioning of organizations in the global marketplace. By leveraging technology and data analytics, organizations can gain insights into market trends, consumer behavior, and competitive dynamics. This enables them to identify opportunities, mitigate risks, and develop strategies to gain a competitive edge.In conclusion, information systems are complex and multifaceted constructs that encompass hardware, software, data, people, and processes. These components work together synergistically to support the operations, decision-making processes, and strategic objectives of organizations. In today's digital age, the effective management andutilization of information systems are essential for achieving success and maintaining competitiveness in the global marketplace.。
英文文件——精选推荐
英⽂⽂件Establishing a management informationsystemInformation is a critical resource in the operation and management of organizations. Timely availability of relevant information is vital for effective performance of managerial functions such as planning, organizing, leading, and control. An information system in an organization is like the nervous system in the human body: it is the link that connects all the organization's components together and provides for better operation and survival in a competitive environment.The term information system usually a computer-based system, one that is designed to support the operations, management, and decision functions of an organization. Information systems in organizations thus provide information support for decision makers. Information systems encompass transaction processing systems, management information systems, decision support systems, and strategic information systems.Information consists of data that have been processed and are meaningful to a user. A system is a set of components that operate together to achieve a common purpose. Thus a management information system collects, transmits, processes, and stores data on an organization's resources, programmes, and accomplishments. The system makes possible the conversion of these data into management information for use by decision makers within the organization. A management information system, therefore, produces information that supports the management functions of an organization (Davis & Olson, 1985; Lucas, 1990; McLeod, 1995).Basic conceptsData versus InformationData refers to raw, unevaluated facts, figures, symbols, objects, events, etc. Data may be a collection of facts lying in storage, like a telephone directory or census records.Information is data that have been put into a meaningful and useful context and communicated to a recipient who uses it to make decisions. Information involves the communication and reception of intelligence or knowledge. It appraises and notifies, surprises and stimulates, reduces uncertainty, reveals additional alternatives or helps eliminate irrelevant or poor ones, and influences individuals and stimulates them to action. An element of data may constitute information in a specific context; for example, when you want to contact your friend, his or her telephone number is a piece of information; otherwise, it is just one element of data in the telephone directory.Characteristics of InformationThe characteristics of good information are relevance, timeliness, accuracy, cost-effectiveness, reliability, usability, exhaustiveness, and aggregation level. Information is relevant if it leads to improved decision making. It might also be relevant if it reaffirms a previous decision. If it does not have anything to do with your problem, it is irrelevant. For example, information about the weather conditions in Paris in January is relevant if you are considering a visit to Paris in January. Otherwise, the information is not relevant.Timeliness refers to the currency of the information presented to the users. Currency of data or information is the time gap between the occurrence of an event in the field until its presentation to the user (decision maker). When this amount of time is very short, we describe the information system as a real-time system.Accuracy is measured by comparing the data to actual events. The importance of accurate data varies with the type of decisions that need to be made. Payroll information must be exact. Approximations simply will not suffice. However, a general estimate of how much staff time was devoted to a particular activity may be all that is needed.Value of InformationInformation has a great impact on decision making, and hence its value is closely tied to the decisions that result from its use. Information does not have an absolute universal value. Its value is related to those who use it, when it is used, and in what situation it is used. In this sense, information is similar to other commodities. For example, the value of a glass of water is different for someone who has lost his way in Arctic glaciers than it is to a wanderer in the Sahara Desert.Economists distinguish value from cost or price of a commodity incurred to produce or procure the commodity. Obviously, the value of a product must be higher than its cost or price for it to be cost-effective.The concept of normative value of information has been developed by economists and statisticians and is derived from decision theory. The basic premise of the theory is that we always have some preliminary knowledge about the occurrence ofevents that are relevant to our decisions. Additional information might modify our view of the occurrence probabilities and consequently change our decision and the expected payoff from the decision. The value of additional information is, hence, the difference in expected payoff obtained by reduced uncertainty about the future event.Information supports decisions, decisions trigger actions, and actions affect the achievements or performance of the organization. If we can measure the differences in performance, we can trace the impact of information, provided that the measurements are carefully performed, the relationships among variables are well defined, and possible effects of irrelevant factors are isolated. The measured difference in performance due to informational factors is called the realistic value or revealed value of information.For most information systems, particularly those supporting middle and top management, the resulting decisions often relate to events that are not strictly defined and involve probabilities that cannot be quantified. The decision-making process often is obscure and the outcomes are scaled by multiple and incomparable dimensions. In such cases, we may either attemptto perform a multiattribute analysis or derive an overall subjective value. The subjective value reflects people's comprehensive impression of information and the amount they are willing to pay for specific information (Ahituv, Neumann, & Riley, 1994).Information as an Aid to Decision MakingSimon (1977) describes the process of decision making as comprising four steps: intelligence, design, choice, and review. The intelligence stage encompasses collection, classification, processing, and presentation of data relating to the organization and its environment. This is necessary to identify situations calling for decision. During the decision stage, the decision maker outlines alternative solutions, each of which involves a set of actions to be taken. The data gathered during the intelligence stage are now used by statistical and other models to forecast possible outcomes for each alternative. Each alternative can also be examined for technological, behavioural, and economic feasibility. In the choice stage, the decision maker must select one of the alternatives that will best contribute to the goals of the organization. Past choices can be subjected to review during implementation and monitoring to enable the manager to learn from mistakes. Information plays an important role in all four stages of the decision process.Classification of Management Information SystemsThere are various types of management information systems. Mason and Swanson (1981) describe four categories of management information systems: (1) databank information system, (2) predictive information system, (3) decision-making information system, and (4) decision-taking information system. The classification is based on the level of support that the information system provides in the process of decision making. Sachdeva (1990) comprehensively presents these four types of systems:Databank Information System.The responsibility of this information system is to observe, classify, and store any item of data which might be potentially useful to the decision maker.Predictive Information System. This system moves beyond pure data collection and the determination of trends over time. Predictive information systems provide for the drawing of inferences and predictions that are relevant to decision making. If data from the above examples were to be used in this way, it is possible to obtain information useful for making predictions or for drawing inferences.Decision-Making Information System. This system goes one step further in the process of decision making and incorporates the value system of the organization or its criteria for choosing among alternatives. An extension organization's values are many and varied. They include concerns for resolving farmer problems, increasing and providing for stability of farmer incomes, and improving the quality of farm life. But they also including and providing for stability of farmer incomes, and improving the quality of farm life. But they also include an intent to provide well for staff members (training, adequate salaries, etc.) and to aid in the process of bringing about rural economic development.Decision-Taking Information System. Examples of decision-taking information systems are not usually found in an extension organization. This is a decisionsystem in which the information system and the decision maker are one and the same. Management is so confident in the assumptions incorporated in the system that it basically relegates its power to initiate action to the system itself. Airplanes carry automatic pilot systems, which are an example of a decision-taking system. Once activated, the system itself keeps the plane on course and at the proper speed and altitude (according to parameters determined by the pilot). Another example of decision-taking information systems is found in modem factory production. In automobile production, continuous inventories of parts are maintained by computer as cars move down an assembly line. Orders are placed automatically by the computer when additional parts are needed. This is done without the intervention of a manager.Role of MIS in the management of agricultural extension programmersNational agricultural extension systems, especially in developing countries, tend to be very large. For example, in India, the national agricultural extension system employs about 125,000 people. Extension managers at various levels need relevant information in order to make effective decisions. In the absence of such information, they act only on the basis of their intuition and past experience. Data that have been processed, stored, and presented properly will aid them in analysing situations and to make effective decisions.As suggested above, at every phase of the management process, managers need information in order to make effective decisions. This we call management information. It does not include purely functional information or technical information, such as packages of practices for rice or wheat cultivation. Management information is the information required by managers as they make their decisions, such as the number of extension personnel employed by category, their training requirements, career development plans, job descriptions, budgets, forecasts, benchmark surveys, reports on socioeconomic conditions of people served, and existing facilities (Ramesh Babu& Singh, 1987).Need for automationAn automated MIS system contains data just as a manual system does. It receives input, processes input, and delivers the processed input as output. Some input devices allow direct human-machine communication, while others require data to be recorded on an input medium such as a magnetizable material (specially coated plastic flexible or floppy disks and magnetic tapes). The keyboard of a workstation connected directly to a computer is an example of a direct input device. Use of automation makes it possible to store immensequantities of information, to avoid many of the errors that find their way into manual records, and to make calculations and comparisons that would be practically impossible in a manual system.Organization of a databaseData are usually generated at the field level throughtransaction-processing systems, but once the data are captured, any echelon along the organizational hierarchy may use them, provided that information requirements have been well defined, appropriate programmers have been implemented, and a means has been arranged for the sharing of the data. This would imply that the same data can be used by different sets of programmers; hence we distinguish between the database (a set of data) and the applications (a set of programmers). In a decision support system (DSS), this set of programmers is the model base (Keen & Morton, 1978).The term database may refer to any collection of data that might serve an organizational unit. A database on a given subject is a collection of data on that subject that observes three criteria: comprehensiveness (completeness), nonredundancy, and appropriate structure. Comprehensiveness means that all the data about the subject are actually present in the database. Nonredundancy means that each individual piece of data exists only once in the database. Appropriate structure means that the data are stored in such a way as to minimize the cost of expected processing and storage(Awad&Gotterer, 1992).The idea of a large corporate database that can be flexibly shared by several applications or model bases has been realized by means of software packages specially devised to perform such tasks. These packages, called database management systems (DBMSs), are available in the market under different trade names such as ORACLE, SYBASE, INGRES, FOXBASE, and dBASE.Database Maintenance (DB Projects)This tab contains links to the administrative modules of five locally created databases.(n3) As with e-journals, records can be added, edited, and deleted, and bulk amounts of data can be imported using delimited files.Bookmarks (Bookmarks on bar beneath the tabs)Since Hobbes displays information based on a librarian's login, we were able to add some tools that provided unique data for a given librarian. For example, each person is able to upload his or her browser bookmarks from the office computer to use at the reference desk or from home. Librarians are also able to upload liaison newsletters into Hobbes, which in turn are displayed on their HDL staff page.THE LOGIC PROGRAMMING OF HobbesLogic programming, which is based on the first-order predicate logic, has been widely used in AI applications, It is a programming style of attractive features. As logic is regarded as a formalism unifying AI, data management and programming, it is the key feature of many new generation projects, especially the FGCS. The principal idea behind logicprogramming is that an algorithm comprises two parts: a logical component and a control component. The users need only to specify in his program what to do (i.e. , the logical component ), whereas it is the responsibility of the system to exercise the control on how to do it.One of the major feature of logic programs is its non-determinisms. Compared with normal programs, logic programs are non-deterministic in two senses:(1)When several clauses match a given procedure call, the search strategy by means of which the alternative clauses are tride is not determined.(2)When several calls need to be executed in a single goal statement, the order of execution is not determined.The non-determinisms of logic programs make them suitable for AI applications (e.g., problem solving ) and potentially rich in parallelism.There is continuous effort in improving the implementation efficiency of Prolog, which is a restriction of logic programming. However, the past effort mainly focuses on interpreter-based software implementation. It is only inrecent years that Prolog oriented computer architectures are developed. The PSI-II in Japan and the PLM at Berkeley are two famous sequential Prolog machines, which are based on the WAM, a high performance compiler-based execution model for Prolog. It is estimated that the highest possible performance of a sequential Prolog machine constructed.In order to meet the demand of gigantic inference speed in AI applications, the inherent parallelisms in logic programs should be exploited. There are many sources of parallelism in logic programs, of which the major ones are the AND-parallelism, the ORparallelism and the stream parallelism. Substantial research has been carried out on parallel computation models utilizing these parallelisms.New logic programming languages suitable for parallel processing have been developed. For example, the Concurrent Prolog, the GHC, the Parlog, the Delta-prolog, etc. special architectures supporting efficient implementation of these languages have been investigated. Besides, multiprocessor systems have been constructed to greatly enhance the performance of parallel processing of logic programs and production systems.THE DATAFLOW COMPUTATION OF HobbesTraditional computers are challenged with application which require tremendously high-speed computation capability, which has led computer scientists to study non vonneumann architectures, of which the most promising one is the dataflow architecture. A dataflow computation is one in which the operations are executed in an order determined by the data interdependencies and the availability of resources. In a dataflow program, the ordering of operations is not specified by the programmer, but is that implied by the data interdependencies.Two varieties of dataflow computation can be distinguished: data-driven computations, and demand-driven computations. In a data-driven computer, an instruction can be executed as soon as the input data it requires are available. After the instruction is executed, its result is made available to the successor instructions. In a demand driven (e.g. , reduction) system, an instruction is triggered when the results produced by it are demanded by other instructions. These demands cause further demands for operands unless the operands are locally available in which case the instruction isexecuted and the results are sent back. In both of these systems, as a result of data (or demand) activated instruction execution, many instructions can become available for execution at once , and it is possible to exploit all of the parallelism in the program. It is expected that these architectures can efficiently exploit concurrency of computation on a very large scale. A number of such systems are being developed around the world. Most notably, the Japanese have chosen dataflow as the underlying architecture for their Fifth Generation Machines. Dataflow and reduction architectures hold great promise, but there are some important problems to be solved before they can be used effectively to provide large scale parallelism. One major problem of dataflow architecture is its heavy overhead. To solve the problem, proposals have been made to combine dataflow with control flow, and to exploit parallelisms at task-level.Illustrative computer-based MISA national agricultural extension system is a nationwide system managed by the national government. In India, agriculture is a state subject under the division of powers between the national and the state levels. Nevertheless, the national government supplements the financial resources of the states and provides coordination at the national level. The state's administrative machinery is divided into districts, districts into subdivisions, subdivisions into blocks. A block is a group of villages and the basic unit for the administration of an agricultural extension programmer. Data collected at the block level need to be integrated at higher administrative levels to provide an integrated view at the district and state levels to support planning, monitoring, and decision making.However, the actual design may vary with the size of the state and other considerations. An integrated database for the entire state may be supportedby a mainframe/minicomputer at the state headquarters. Suitable programmes for the analysis of data may be designed to provide an interactive decision support system at the state level. Each district and subdivision may be provided with amini/micro computer, depending on the volume of data to be handled. The computers in the districts and subdivisions may be networked with the state computer. The local data may be stored and processed in the district/subdivision, and the shared data with appropriate level of aggregation may be transmitted to the state headquarters to update the integrated database. The districts and subdivisions would have direct access to the integrated database with proper authorizations assigned to them through their passwords. The blocks may have only the input-output terminals connected to the subdivision computer to feed data to the subdivision and make on-line inquiries as and when necessary.ReferencesAhituv, N., Neumann, S., & Riley, H. N. (1994). Principles of information systems for management (4th ed.). Dubuque, IA: Wm. C. Brown Communications.Awad, E. M., &Gotterer, M. H. (1992). Database management. Danvers, MA: Boyd & Fraser.Banerjee, U. K., &Sachdeva, R. K. (1995). Management information system: A new frame work. New Delhi: Vikas Publishing House.Davis, G.B., & Olson, M. H. (1985). Management information systems: Conceptual foundations, structure, and development. New York:McGraw-Hill.Imboden, N. (1980). Managing information for rural development projects. Paris: Organization for Economic Co-operation and Development.Keen, P. G. W., & Morton, M. S. S. (1978). Decision support systems. Reading, MA: Addison-Wesley.Lucas, H. C., Jr. (1990). Information systems concepts for management. New York: McGraw-Hill.Martin, J. (1990). Telecommunications and the computer (3rd ed.). Englewood Cliffs, NJ: Prentice-Hall.Mason, R. D., & Swanson, B. E. (1981). Measurements for management decision. Reading, MA: Addison-Wesley. McLeod, R., Jr. (1995). Management information systems: A study of computer-based information systems (6th ed.). New Delhi: Prentice Hall of India.Raheja, S. K., & Jai Krishna (1991). Manual for monitoring and evaluation of T & V agricultural extension system. New Delhi: Centre for Agricultural and Rural Development Studies.Ramesh Babu, A., & Singh, Y. P. (1987). Management information system in an agricultural extension organization. In Proceedings of the national seminar on management of information system in management of agricultural extension (p. 1-15). Hyderabad: NIRD.Ramesh Babu, A., & Singh, Y. P. (1990). Agricultural administration at block level: A case study. Indian Journal of Extension Education, 26 (1 & 2), 88-90. Rao, C. S. S. (1985). Agricultural extension management system in India: Past, present and modalities in future. Indian Journal of Extension Education, 21 (1 & 2), 32-35.Russell, H. M. (1979). A review of management information systems for agriculture. In H. M. Russell (Ed.), Information for agriculture: Proceedings of the national workshop on agricultural information (p. 41-51). Melbourne: Department of Agriculture, Victoria.Sachdeva, R. K. (1990). Management handbook of computer usage. Oxford: NCC Blackwell.Sanders, D. H. (1988). Computers today (3rd ed.). New York: McGraw-Hill. Simon, H. A. (1977). The new science of management decision. New Jersey: Prentice-Hall.Singh, Y. P., & Ramesh Babu, A. (1985). Basic management issues in extension. Indian Journal of Extension Education, 27 (1 & 2), 20-31.Wentling, T. L., &Wentling, R. M. (1993). Introduction to microcomputer technologies. Rome: FAO.。
DSS-review决策支持系统
Chapter 1Management Support Systems:An OverviewProductivity•The ratio of outputs to inputs that measures the degree of success of an organization and its individual partsFactors Affecting Decision-Making•New technologies and better information distribution have resulted in more alternatives for management.•Complex operations have increased the costs of errors, causing a chain reaction throughout the organization.•Rapidly changing global economies and markets are producing greater uncertainty and requiring faster response in order to maintain competitive advantages.•Increasing governmental regulation coupled with political destabilization have caused great uncertainty.What do Decision Support Systems Offer?•Quick computations at a lower cost•Group collaboration and communication•Increased productivity•Ready access to information stored in multiple databases and data warehouse •Ability to analyze multiple alternatives and apply risk management •Enterprise resource management•Tools to obtain and maintain competitive advantageCognitive Limits•The human mind has limited processing and storage capabilities.•Any single person is therefore limited in their decision making abilities. •Collaboration with others allows for a wider range of possible answers, but will often be faced with communications problems.•Computers improve the coordination of these activities.•This knowledge sharing is enhanced through the use of GSS, KMS, and EIS.Management Support Systems•The support of management tasks by the application of technologies – Sometimes called Decision Support Systems or BusinessIntelligenceManagement Support Systems Tools•DSS•Management Science•Business Analytics•Data Mining•Data Warehouse•Business Intelligence•OLAP•CASE tools•GSS•EIS•EIP•ERM•ERP•CRM•SCM•KMS•KMP•ES•ANN•Intelligent Agents•E-commerce DSSDecision Support FrameworksTechnologies for Decision-Making Processes Technology Support Based on Anthony’s TaxonomyEnterprise Information Systems•Evolved from Executive Information Systems combined with Web technologies•EIPs view information across entire organizations•Provide rapid access to detailed information through drill-down.•Provide user-friendly interfaces through portals.•Identifies opportunities and threatsEnterprise Information Systems •Specialized systems include ERM, ERP, CRM, and SCM •Provides timely and effective corporate level tracking and control. •Filter, compress, and track critical data and information.Knowledge Management Systems •Knowledge that is organized and stored in a repository for use by an organization•Can be used to solve similar or identical problems in the future •ROIs as high as a factor of 25 within one to two yearsExpert Systems•Technologies that apply reasoning methodologies in a specific domain •Attempts to mimic human experts’ problem solvingEmerging Technologies•Grid computing•Improved GUIs•Model-driven architectures with code reuse•M-based and L-based wireless computing•Intelligent agents•Genetic algorithms•Heuristics and new problem-solving techniquesChapter 2Decision-Making Systems, Models, and SupportDecision Making•Process of choosing amongst alternative courses of action for the purpose of attaining a goal or goals.•The four phases of the decision process are:– Intelligence– Design– Choice– implementationSystems•Structure– Inputs– Processes– Outputs– Feedback from output to decision maker•Separated from environment by boundary •Surrounded by environmentSystem Types •Closed system– Independent– Takes no inputs– Delivers no outputs to the environment– Black Box•Open system– Accepts inputs– Delivers outputs to environmentModels Used for DSS •Iconic– Small physical replication of system •Analog– Behavioral representation of system– May not look like system•Quantitative (mathematical)– Demonstrates relationships between systemsPhases of Decision-Making •Simon’s original three phases:– Intelligence– Design– Choice•He added fourth phase later:– Implementation•Book adds fifth stage:– MonitoringDecision-Making Intelligence Phase •Scan the environment•Analyze organizational goals•Collect data•Identify problem•Categorize problem– Programmed and non-programmed– Decomposed into smaller parts•Assess ownership and responsibility for problem resolutionDecision-Making Design Phase•Develop alternative courses of action•Analyze potential solutions•Create model•Test for feasibility•Validate results•Select a principle of choice–Incorporate into models–Risk assessment and acceptanceDecision-Making Choice Phase•Principle of choice– Describes acceptability of a solution approach•Normative Models– Optimization– Rationalization•Courses of action are known quantity•Options ranked from best to worse– Suboptimization•Decisions made in separate parts of organization without consideration of wholeDescriptive Models•Describe how things are believed to be•Typically, mathematically based•Applies single set of alternatives•Examples:– Simulations– What-if scenarios– Cognitive map– NarrativesDeveloping Alternatives •Generation of alternatives– May be automatic or manual– May be legion, leading to information overload– Scenarios– Evaluate with heuristics– Outcome measured by goal attainmentDecision-Making Choice Phase •Decision making with commitment to act•Determine courses of action– Analytical techniques– Algorithms– Heuristics– Blind searches•Analyze for robustnessDecision-Making Implementation Phase •Putting solution to work•Vague boundaries which include:– Dealing with resistance to change– User training– Upper management supportDecision Support Systems •Intelligence Phase– Automatic•Data Mining–Expert systems, CRM, neural networks– ManualDecision Support Systems•Design Phase– Financial and forecasting models– Generation of alternatives by expert system– Relationship identification through OLAP and data mining – Business process models from CRM, RMS, ERP, and SCMDecision Support Systems•Choice Phase– Identification of best alternative– Identification of good enough alternative– What-if analysis– May use KMS, GSS, CRM, ERP, and SCM systemsDecision Support Systems •Implementation Phase– Improved communications– Collaboration– Training– Supported by KMS, expert systems, GSSChapter 3Decision Support Systems: An OverviewDSS• A DSS is a methodology that supports decision-making.•It is:– Flexible;– Adaptive;– Interactive;– GUI-based;– Iterative;– Employs modeling.Components of DSS •Subsystems:– Data management•Managed by DBMS– Model management•Managed by MBMS– User interface– Knowledge Management and organizational knowledge baseData Management Subsystem•Components:– Database– Database management system– Data directory– Query facilityDatabase•Interrelated data extracted from various sources, stored for use by the organization, and queried– Internal data, usually from TPS– External data from government agencies, trade associations,market research firms, forecasting firmsDatabase Management System•Extracts data•Manages data and their relationships•Updates (add, delete, edit, change)•Retrieves data (accesses it)•Queries and manipulates data•Employs data dictionaryData Directory•Catalog of all data– Contains data definitions– Answers questions about the availability of data items– Source– Meaning– Allows for additions, removals, and alterationsModel Management Subsystem•Components:– Model base– Model base management system– Modeling language– Model directory– Model execution, integration, and command processorModels•Strategic– Supports top management decisions•Tactical– Used primarily by middle management to allocate resources •Operational– Supports daily activities•Analytical– Used to perform analysis of dataModel Base Management System •Functions:– Model creation– Model updates– Model data manipulation– Generation of new routines•Model directory:– Catalog of models– DefinitionsModel Management Activities•Model execution– Controls running of model•Model command processor– Receives model instructions from user interface– Routes instructions to MBMS or module execution or integration functions•Model integration–Combines several models’ operationsUser Interface SystemUser Interface Management System•GUI•Natural language processor•Interacts with model management and data management subsystems•Examples–Speech recognition–Display panel–Tactile interfacesKnowledge-Based Management System•Expert or intelligent agent system component•Complex problem solving•Enhances operations of other components•May consist of several systems•Often text-oriented DSSDSS Classifications•Alte r– Extent to which outputs can directly support or determine thedecision– Data oriented or model oriented•Holsapple and Whinston– Text oriented, database oriented, spreadsheet oriented, solver oriented, rule oriented, or compound•Donovan and Madnick– Institutional– Problems of recurring nature•GSS v. Individual DSS– Decisions made by entire group or by lone decision maker •Custom made v. vendor ready made– Generic DSS may be modified for useChapter 4Modeling and Analysis•Promodel simulation created representing entire transport system •Applied what-if analyses•Visual simulation•Identified varying conditions•Identified bottlenecks•Allowed for downsized fleet without downsizing deliveriesMSS Modeling•Key element in DSS•Multiple models often included in a DSS•Can be object-oriented•Enhances decision makingDSS Models•Algorithm-based models•Statistic-based models•Linear programming models•Graphical models•Quantitative models•Qualitative models•Simulation modelsProblem Identification •Environmental scanning and analysis•Business intelligence•Identify variables and relationships– Influence diagrams– Cognitive maps•Forecasting– Fueled by e-commerce– Increased amounts of information available through technologyStatic Models•Single photograph of situation•Single interval•Time can be rolled forward, a photo at a time•Usually repeatable•Steady state– Optimal operating parameters– Continuous– Unvarying– Primary tool for process designDynamic Model•Represent changing situations•Time dependent•Varying conditions•Generate and use trends•Occurrence may not repeatDecision-Making•Certainty– Assume complete knowledge– All potential outcomes known– Easy to develop– Resolution determined easilyUncertainty– Several outcomes for each decision– Probability of occurrence of each outcome unknown– Insufficient information•Probabilistic Decision-Making– Decision under risk– Probability of each of several possible outcomes occurring – Risk analysisInfluence Diagrams•Graphical representation of model•Provides relationship framework•Examines dependencies of variables•Any level of detail•Shows impact of change•Shows what-if analysisDecisionIntermediateoruncontrollableVariables:CertaintyUncertaintyArrows indicate type of relationship and direction of influenceModeling with Spreadsheets•Flexible and easy to use•End-user modeling tool•Allows linear programming and regression analysis •Features what-if analysis, data management, macros •Seamless and transparent•Incorporates both static and dynamic modelsDecision Tree•Graphical representation of relationships•Multiple criteria approach•Demonstrates complex relationships•Cumbersome, if many alternativesMSS Mathematical Models•Link decision variables, uncontrollable variables, parameters, and result variables together•Nonquantitative models– Symbolic relationship– Qualitative relationship– Results based upon•Decision selected•Factors beyond control of decision maker •Relationships amongst variablesSensitivity, What-if, and Goal Seeking Analysis •Sensitivity•What-if•Goal seekingSearch Approaches•Analytical techniques (algorithms) for structured problems – General, step-by-step search– Obtains an optimal solution•Blind search– Complete enumeration– Incomplete– Achieves particular goal– May obtain optimal goal•Heurisitic– Repeated, step-by-step searches– Rule-based, so used for specific situations–“Good enough” solution, but, eventually, will obtain optimal goal – Examples of heuristics•Tabu search–Remembers and directs toward higher quality choices•Genetic algorithms–Randomly examines pairs of solutions and mutationsSimulations•Imitation of reality•Allows for experimentation and time compression •Descriptive, not normative•Can include complexities, but requires special skills•Handles unstructured problems•Optimal solution not guaranteed•Methodology–Problem definition–Construction of model–Testing and validation–Design of experiment–Experimentation–Evaluation–Implementation•Probabilistic independent variables– Discrete or continuous distributions•Time-dependent or time-independent•Visual interactive modeling– Graphical– Decision-makers interact with simulated model– may be used with artificial intelligence•Can be objected orientedModel-Based Management System•Software that allows model organization with transparent data processing•Capabilities– DSS user has control– Flexible in design– Gives feedback– GUI based– Reduction of redundancy– Increase in consistency– Communication between combined models•Relational model base management system– Virtual file– Virtual relationship•Object-oriented model base management system– Logical independence•Database and MIS design model systems– Data diagram, ERD diagrams managed by CASE toolsChapter 5Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization •Network of systems that provide knowledge integration and distribution•Horizontal and vertical information sharing•Mining of data stored in Web-enabled warehouseData, Information, Knowledge•Data– Items that are the most elementary descriptions of things, events, activities, and transactions– May be internal or external•Information– Organized data that has meaning and value•Knowledge– Processed data or information that conveys understanding or learning applicable to a problem or activityData•Raw data collected manually or by instruments•Quality is critical– Quality determines usefulness– Often neglected or casually handled– Problems exposed when data is summarized•Cleanse data– When populating warehouse– Data quality action plan– Best practices for data quality– Measure results•Data integrity issues– Uniformity– Version– Completeness check– Conformity check– Genealogy or drill-down•Data Integration•Access needed to multiple sources– Often enterprise-wide– Disparate and heterogeneous databases– XML becoming language standardExternal Data Sources•Web– Intelligent agents– Document management systems– Content management systems•Commercial databases– Sell access to specialized databasesDatabase Management Systems •Software program•Supplements operating system•Manages data•Queries data and generates reports•Data security•Combines with modeling language for construction of DSSDatabase Models•Hierarchical•Network•Relational•Object orientedData Warehouse•Subject oriented•Scrubbed so that data from heterogeneous sources are standardized •Time series; no current status•Nonvolatile–Read only•Summarized•Not normalized; may be redundant•Data from both internal and external sources is present•Metadata included–Data about data•Business metadata•Semantic metadataArchitecture•May have one or more tiers– Determined by warehouse, data acquisition (back end), and client (front end)•One tier, where all run on same platform, is rare•Two tier usually combines DSS engine (client) with warehouse –More economical•Three tier separates these functional partsData Marts•Dependent– Created from warehouse– Replicated•Functional subset of warehouse•Independent– Scaled down, less expensive version of data warehouse– Designed for a department or SBU– Organization may have multiple data martsBusiness Intelligence and Analytics •Business intelligence– Acquisition of data and information for use in decision-makingactivities•Business analytics– Models and solution methods•Data mining– Applying models and methods to data to identify patterns andtrendsOLAP•Activities performed by end users in online systems•Modeling and visualization capabilities•Special class of toolsData Mining•Organizes and employs information and knowledge from databases •Statistical, mathematical, artificial intelligence, andmachine-learning techniques•Automatic and fast•Tools look for patterns– Simple models– Intermediate models– Complex Models•Data mining application classes of problems–Classification–Clustering–Association–Sequencing–Regression–Forecasting–OthersTools and Techniques•Data mining– Statistical methods– Decision trees– Case based reasoning– Neural computing– Intelligent agents– Genetic algorithmsKnowledge Discovery in Databases•Data mining used to find patterns in dataData Visualization•Technologies supporting visualization and interpretation – Digital imaging, GIS, GUI, tables, multidimensions, graphs, VR,3D, animation– Identify relationships and trendsGIS•Computerized system for managing and manipulating data with digitized maps– Geographically oriented– Geographic spreadsheet for models– Software allows web access to maps– Used for modeling and simulationsChapter 6Decision Support System DevelopmentSystems Development Life Cycle•Four phases– Planning– Analysis– Design– Implementation•Cyclical•Can return to other phases•Waterfall modelTools•Computer-aided software design tools–Upper CASE –•Creates systems diagrams–Lower CASE•Manages diagrams and code–Integrated CASE•Combination•RAD design tools–Enterprise class repository and collaboration–UML modeling•Analysis and design software•Code debugging methods•Testing and quality assurance toolsSuccessful Project Management •Establish a baseline•Define scope of project•Manage change and scope creep•Get support from upper management•Establish timelines, milestones, and budgets based on realistic goals•Involve users•Document everythingProject Management Tools•Project management software can allow:– Collaboration among disparate teams– Resource and program management– Portfolio management– Web enabled– Aggregates and analyses project dataDSS Development Methodology •Prototyping•Iterative design•Evolutionary development•Middle out process•Adaptive design•Incremental designDSS Prototyping•Short steps– Planning– Analysis– Design– Prototype•Immediate stakeholder feedback•Iterative– In development of prototype– Within the system in general•Advantages–User and management involvement–Learning explicitly integrated–Prototyping bypasses information requirement–Short intervals between iterations–Low cost–Improved user understanding of systemAgile Development•Rapid prototyping•Used for:– Unclear or rapidly changing requirements– Speedy developmentDSS Technology Levels•DSS primary tools–Fundamental elements•Programming languages, graphics, editors, query systems•DSS generator (engine)–Integrated software package for building specific DSS•Modeling, report generation, graphics, risk analysis•Specific DSS–DSS application that accomplishes the work•DSS primary tools are used to construct integrated tools that are used to construct specific toolsDSS•Hardware– PCs to multiprocessor mainframes•Software– Involves multiple criteria– Develop in house, outsource, or buy off the shelf– Off the shelf software rapidly updated; many on market– Prices fluctuate– Different tools available•Team developed DSS requires substantial effort to build and manage•End user developed DSS– Decision-makers and knowledge workers develop to solve problems orenhance productivity•Advantages–Short delivery time–User requirements specifications are eliminated–Reduced implementation problems–Low costs•Risks–Quality may be low–May have lack of documentation–Security risks may increase•DSS is much more than just a DBMS, MBMS, GUI, interface, and knowledge component21。
餐饮管理决策英语术语
餐饮管理决策英语术语1. IntroductionIn the field of food and beverage management, there are numerous English terms that are commonly used to describe different aspects of decision-making. This document aims to provide an overview of some key terms related to decision-making in the food service industry.2. Menu EngineeringMenu engineering is a strategic approach to designing and pricing menus to maximize profitability. It involves analyzing the popularity and profitability of menu items to make informed decisions about pricing, promotion, and placement.3. Cost ControlCost control is the process of managing expenses to ensure that they are within budgeted limits. In the context of food and beverage management, cost control involves monitoring food and labor costs, and taking corrective actions to reduce expenses without compromising quality.4. ForecastingForecasting is the process of making predictions about future sales, expenses, and other factors that impact business operations. In the food service industry, accurate forecasting is essential for planning menus, staffing levels, and purchasing decisions.5. Inventory ManagementInventory management involves tracking and controlling the flow of food and beverage items in a restaurant or food service operation. Effective inventory management helps to minimize waste, prevent stockouts, and maintain optimal stock levels.6. Pricing StrategyPricing strategy refers to the method of setting prices for menu items to achieve specific business objectives. Common pricing strategies in the food service industry include cost-plus pricing, competitive pricing, and value-based pricing.7. Revenue ManagementRevenue management is a strategic approach to maximizing revenue through pricing and capacity management. In the context of food and beverage management, revenue management involves adjusting prices based on demand, seasonality, and other factors to optimize sales and profitability.8. Yield ManagementYield management is a pricing strategy that involves adjusting prices based on demand to maximize revenue. In the food service industry, yield management is used to optimize seating capacity, menu pricing, and promotions to drive sales and profits.9. Decision Support SystemsDecision support systems are software tools that help managers make informed decisions by providing data analysis, forecasting, and other decision-making support. In the food service industry, decision support systems can assist in menu planning, inventory management, and financial analysis.10. ConclusionThe successful management of a food and beverage operation requires a deep understanding of key decision-making concepts and English terms. By applying menu engineering, cost control, forecasting, and other strategies discussed in this document, food service managers can make informed decisions to drive profitability and operational efficiency.。
国际学术期刊
附录1：东北大学工商管理学院博士研究生发表学术论文量化标准认定的国际学术期刊目录（2012年4月制订）工商管理学院博士研究生发表学术论文量化标准认定的国际学术期刊目录（各学科通用标准），分为3个级别，即国际A级期刊、国际B级期刊和国际C级期刊。
其中，国际A级期刊（可再分为A+级和A级）和国际B级期刊（可再分为B+级和B级）参见下列目录清单，国际C期刊为不在下列清单的SCI或SSCI检索源的学术期刊（不包括国内大学学报英文版）。
1、会计（Accounting）A+级：Accounting ReviewAccounting, Organizations and SocietyContemporary Accounting ResearchJournal of Accounting ＆EconomicsJournal of Accounting ResearchReview of Accounting StudiesA级：Auditing: A Journal of Practice ＆TheoryJournal of Accounting & Public PolicyJournal of Accounting, Auditing ＆FinanceJournal of Business Finance and AccountingJournal of Management Accounting ResearchJournal of the American Taxation AssociationB+级：AbacusAccounting ＆FinanceAccounting and Business ResearchAccounting HorizonsAccounting, Auditing and AccountabilityAsia-Pacific Journal of Accounting and EconomicsBehavioral Research in AccountingBritish Accounting ReviewCritical Perspectives in AccountingFinancial Accountability and ManagementThe International Journal of AccountingInternational Journal of AuditingJournal of Accounting LiteratureJournal of Information SystemsJournal of International Accounting ResearchJournal of International Accounting, Auditing ＆TaxationJournal of International Financial ManagementNational Tax JournalB级：Accounting Education: An International JournalChina Accounting and Finance ReviewEuropean Accounting ReviewInternational Tax JournalIssues in Accounting EducationJournal of Accounting EducationManagerial AuditingPacific Accounting Review2、经济（Economics）A+级：American Economic ReviewEconometricaEconomic JournalJournal of Economic TheoryJournal of Political EconomyQuarterly Journal of EconomicsReview of Economic StudiesThe Review of Economics and StatisticsA级：Canadian Journal of EconomicsEconometric TheoryEuropean Economic ReviewGames ＆Economic BehaviorInternational Economic ReviewJournal of Applied EconometricsJournal of Business and Economic StatisticsJournal of Development EconomicsJournal of EconometricsJournal of Economic Behavior＆OrganizationJournal of Economic Dynamics and ControlJournal of Environmental Economics and ManagementJournal of Health EconomicsJournal of Human ResourcesJournal of International EconomicsJournal of Labor EconomicsThe Journal of Law and EconomicsJournal of Monetary EconomicsJournal of Money，Banking and CreditJournal of Public EconomicsJournal of Urban EconomicsRand Journal of EconomicsReview of Economic DynamicsB+级：China Economic ReviewChina QuarterlyEconomic Development＆Cultural ChangeEconomic InquiryEconomic TheoryEconomicaEconomics LettersEconomics of Education ReviewHealth EconomicsJournal of Comparative EconomicsJournal of Economic GrowthJournal of Economic HistoryJournal of Economic LiteratureJournal of Economic PerspectivesJournal of Industrial EconomicsJournal of Law, Economics＆OrganizationJournal of Mathematical EconomicsJournal of Population EconomicsJournal of Regional ScienceJournal of Risk and UncertaintyLabor EconomicsNational Tax JournalOxford Bulletin of Economics and StatisticsOxford Economic PapersPacific Economic ReviewPublic ChoiceRegional Science ＆Urban EconomicsReview of International EconomicsScandinavian Journal of EconomicsSocial Choice and WelfareSouthern Economics JournalB级：Applied EconomicsCambridge Journal of EconomicsContemporary Economic PolicyEconometric ReviewsEconomic RecordEconomics of TransitionJournal of Transport Economics and PolicyJournal of Economic IssuesJournal of Housing EconomicsJournal of International Trade＆Economic DevelopmentJournal of MacroeconomicsInternational Review for Social SciencesLand EconomicsManagerial and Decision EconomicsReview of Development EconomicsReview of Income and WealthThe Econometrics JournalWorld DevelopmentWorld Economy3、金融（Finance）A+级：Journal of FinanceJournal of Financial and Quantitative AnalysisJournal of Financial EconomicsReview of Financial StudiesA级：Financ ial ManagementJournal of Banking and FinanceJournal of Corporate FinanceJournal of Empirical FinanceJournal of Financial IntermediationJournal of Financial MarketsJournal of International Money and FinanceJournal of Risk and InsuranceMathematical FinanceReal Estate EconomicsB+级：AREUEAEuropean Financial ReviewFinancial Analysts JournalFinancial ReviewInternational Review of FinanceJournal of Applied Corporate FinanceJournal of DerivativesJournal of Financial EngineeringJournal of Financial ResearchJournal of Financial Services ResearchJournal of Fixed IncomeJournal of Futures MarketJournal of Mathematical FinanceJournal of Portfolio ManagementJournal of Real Estate Finance＆EconomicsPacific Basin Finance JournalQuantitative FinanceReview of Quantitative Finance and AccountingB级：Advances in Working Capital ManagementEuropean Journal of FinanceFinancial Practice and EducationFinancial Services ReviewGlobal Finance JournalInternational Journal of FinanceJournal of Bank ResearchJournal of Financial EducationJournal of Real Estate Research4、酒店和旅游管理（Hospitality and Catering／Hotel and T ourism Management）A+级：Annals of Tourism ResearchInternational Journal of Hospitality ManagementA级：Cornell Hospitality QuarterlyJournal of Hospitality and Tourism ResearchJournal of Travel ResearchTourism ManagementB+级：International Journal of Contemporary Hospitality ManagementJournal of Hospitality and Tourism ManagementTourism and Hospitality ResearchTourism EconomicsB级：International Journal of Tourism ResearchJournal of Leisure ResearchJournal of Sustainable TourismJournal of Travel and Tourism Marketing5、管理信息系统（Management Information Systems）A+级：MIS QuarterlyInformation Systems ResearchJournal of Management Information SystemsA级：ACM Transactions on Information SystemsCommunications of the ACMDecision Support SystemsInformation and ManagementThe Journal of American Society for Information Science and TechnologyB+级：European Journal of Information SystemFuzzy Sets and SystemsGroup Decision and Negotiation JournalIEEE Transactions on Systems, Man and Cybernetics (Parts A-C)Information Systems JournalInternational Journal and Electronic CommerceInternational Journal of Human Computer StudiesJournal of Behavioral Decision MakingExpert Systems with ApplicationsInformation SciencesJournal of Organizational Computing and ElectronicJournal of Strategic Information SystemsJournal of the Association for Information SystemsTelecommunications PolicyB级：International Journal of Information Technology & Decision Making Journal of IT Cases and ApplicationsJournal of Organization and End User ComputingJournal of Systems Management6、组织（企业）管理（Management / Organizational Management）A+级：Academy of Management JournalAcademy of Management ReviewAdministrative Science QuarterlyJournal of Management StudiesOrganization ScienceStrategic Management JournalAmerican Journal of SociologyAmerican Sociological ReviewJournal of Applied PsychologyJournal of Personality and Social PsychologyA级：Academy of Management Learning and EducationHarvard Business ReviewHuman RelationsHuman Resource ManagementIndustrial and Labor Relations ReviewJournal of ManagementJournal of Organizational BehaviorOrganizational Behavior and Human Decision Processes0rganizational StudiesPersonnel PsychologyResearch in Organizational BehaviorB+级：Academy of Management PerspectiveAsia Pacific Journal of Human ResourcesAsia Pacific Journal of ManagementBritish Journal of Industrial RelationsBritish Journal of ManagementBusiness HorizonsCalifornia Management ReviewGroup and Organization ManagementIndustrial RelationsInternational Journal of Human Resources ManagementInternational Journal of Selection and AssessmentJournal of Applied Social PsychologyJournal of Business EthicsJournal of Business ResearchJournal of Conflict ResolutionJournal of General ManagementJournal of Occupational and Organizational PsychologyJournal of V ocational BehaviorLeadership QuarterlyManagement and Organization ReviewOrganization0rganizationaI DynamicsOrganizational Research MethodsSloan Management ReviewWork and OccupationsB级：Asia Pacific Business ReviewHuman Resource PlanningInternational Journal of Employment StudiesInternational Journal of Management StudiesInternational Journal of Strategic ManagementInternational Studies of Management and OrganizationLeadership ＆Organization Development JournalSAM Advanced Management Journal7、营销（Marketing / International Business）A+级：Journal of Consumer ResearchJournal of International Business StudiesJournal of MarketingJournal of Marketing ResearchMarketing ScienceA级：International Business ReviewInternational Journal of Research in MarketingJournal of Academy of Marketing ScienceJournal of AdvertisingJournal of Advertising ResearchJournal of Consumer PsychologyJournal of International MarketingJournal of RetailingJournal of World BusinessManagement International ReviewB+级：Asia Pacific Journal of ManagementEuropean Journal of MarketingIndustrial Marketing ManagementInternational Journal of AdvertisingInternational Marketing ReviewJournal of Consumer AffairsJournal of Consumer MarketingJournal of Global MarketingJournal of International Consumer MarketingJournal of International ManagementJournal of Market Research SocietyJournal of Marketing EducationJournal of Marketing ManagementJournal of Personal Selling and Sales ManagementJournal of Product Innovation ManagementJournal of Public Policy and MarketingJournal of Services MarketingMarketing LettersPsychology and MarketingThunderbird International Business ReviewB级：International Studies of Management and OrganizationJournal of Teaching in International BusinessMarketing Intelligence & PlanningMultinational Business ReviewPublic Relations Review8、运作管理/工程管理（Operations Operations / Engineering Mnagement）A+级：Management ScienceOperational ResearchManufacturing ＆Service Operations ManagementProduction and Operations ManagementMathematical ProgrammingMathematics of Operations ResearchA级：Decision ScienceJournal of Operations ManagementEuropean Journal of Operational ResearchIIE TransactionslNFORMS Journal on ComputingNaval Research LogisticsJournal of Product Innovation ManagementTransportation ScienceB+级：Annals of Operation ResearchOperations Research LettersComputers and Operations ResearchIEEE Transactions on Engineering ManagementInterfacesInternational Journal of Production EconomicsInternational Journal of Production ResearchJournal of Optimization Theory and ApplicationsJournal of SchedulingJournal of the Operational Research SocietyNetworksQueueing SystemsStochastic Processes and Their ApplicationsTransportation Research (Parts A-F)Omega — The International Journal of Management ScienceTechnovationB级：Asia Pacific Journal of Operational ResearchComputers and Industrial EngineeringINFOR-Canadian Journal of Operations ResearchInternational Journal of Operations and Production ManagementInternational Journal of Quality and Reliability ManagementProduction Planning and ControlTotal Quality Management and Business ExcellenceErgonomicsJournal of Engineering and Technology ManagementR&D Management9、统计学（Statistics & Probability）A+级：Annals of Applied ProbabilityAnnals of ProbabilityAnnals of StatisticsBiometrikaJournal of American Statistical AssociationJournal of Royal Statistical Society (Series B)A级：Advances in Applied ProbabilityBiometricsJournal of Applied ProbabilityStatistical SinicaB+级：Communication in Statistics — Theory and MethodsComputational Statistics and Data AnalysisInternational Journal of ForecastingInternational Statistical ReviewJournal of Applied StatisticsJournal of Business and Economic StatisticsJournal of Computational and Graphical StatisticsJournal of ForecastingJournal of Multivariate AnalysisJournal of Royal Statistical Society (Series A and C)Journal of Statistical Planning and InferenceJournal of Time Series AnalysisSankhyaScandinavian Journal of StatisticsStatistical ScienceStatistics and ComputingStatistics and Probability LettersTechnometricsTheory of Probability and Its ApplicationsB级：American StatisticiansAnnals of Institute of Statistical MathematicsCanadian Journal of StatisticsInternational Journal of Game Theory。
MIS
1.Concept of Information System: An information system can be any organized combination ofpeople , hardware, software, communications networks ,and data resources that collects, transforms, and disseminates information in an organization.2.Framework of IS: Foundation concepts, Information Technologies, Management challenges,Business Applications, Development Processes.3.Resources of IS: people(end users, specialists), hardware(computer system, computerperipherals), software(system software, application software, procedures), data, networks(communications media , network support).4.Activities of IS: input (of data resource) , processing(of data information) , output(ofinformation products) , storage(of data resources) , control(of system performance).5.Roles of IS:1) support of its business processes and operations2) support of decision making by its employees and managers3) support of its strategies for competitive advantages6. Types of IS: Operations Support systems (Transaction Processing System, Process Control System, Enterprise Collaboration System), Management Support Systems (Management Support System, Decision Support System , Executive Support System), Other Catergories of Information System(Expert systems , Knowledge management systems , Strategic information systems, Functional business systems)7. Trends of IS: Data Processing(1950s-1960s,Electranic data processing system), Management Reporting(1960s-1970s, Management Information system ),Decision Support(1970s-1980s, Decision Support systems),Strategic and End User Support(1980s-1990s, End user computing systems, Executive information systems, Expert systems, Strategic information systems),Electronic Business and Commerce(1990s-2000s, Internetworked e-business and e-commerce systems)8. Five basic competitive strategies: Cost leadership Strategy, Differentiation Strategy, Innovation Strategy, Growth Strategies, Alliance Strategies9. Strategic Uses of IT: Lower costs, differentiate, Innovate, promote growth, develop alliances.10. Other competitive strategies: locking in customers or suppliers, building switching costs, raising barriers to entry, leveraging investment in information technology.11. Strategic Uses of IT for strategic advantage:1)building a customer-focused e-business 2)reengineering business processes 3) improving business quality 4)becoming an agile company 5)creating a virtual company 6)building a knowledge-creating company12.Functional e-business systems: Marketing systems , Human resource systems, Manufacturing systems , Accounting systems , Financial management systems13.Other forms of cross-functional e-business systems : enterprise application integration , online transaction processing , enterprise collaboration14.Types of software15.Operating System basic functions:16Data resource management: a managerial activity that applies information technologies like database management, data warehousing, and other data management tools to the task of managing an organization's data resources to meet the information needs of the business stakeholders17.The four major uses of a DBMS : database development, database interrogation(询问), database maintenance, and application development.18. Database Structures:Hierarchical , Network , Relational , Object-oriented , Multidimensional19. Data element: Character , Field or data item , Record,File or table , Database20. The database management approach involves three basic activities:1) Updating and maintaining common database.2) Providing information needed for each end user’s application by using applicationprograms that share the data in common database.3) Providing an inquiry/response and reporting capability.21. E-business application architecture22.Functional business systems: A variety of information systems (transaction processing, management information systems, decision support, etc.) That support the business functions of Accounting, finance, marketing, operations management and human resource management. 23. Enterprise Resource Planning is a cross-functional enterprise system with an integrated suite of software modules that support the basic internal business processes of a company24. Supply Chain Management (SCM) is a cross-functional interenterprise system to help support and manage the links between a company’s key business processes and those of its suppliers, customers and business partners25. Online Transaction Processing (OTP) is a cross-functional information system using the Internet, extranets, and other networks that tie them electronically to their customers or suppliers.26.Systems Development Lifecycle(also called information systems development cycle)27.Prototyping Life Cycle。
软件工程-外文翻译
The strategic role of management information systemsAfter studying this chapter, you will be able to:1。
Analyze six major information systems in the organizations。
2。
Describe the relationship among various types of information systems。
3。
Understand the characteristics of a strategic information system.4。
Describe how information systems in business strategy to be used for three layers.5。
Explain the problem of the establishment and maintenance of strategic information systems.Orchids Paper Company ----- return to the right directionOrchids Paper Co.Ltd. has been a lower cost paper manufacturer which produces napkin,handkerchief paper, tissues and toilet paper for fifty years. However, in the middle of 1990s, the company lost its developmental way. To take good advantage of the prosperous economic situation in the late twentieth century in the 80's, employers began to squeeze into the ascendant private-label paper market in California (the company headquarters at that time). Unfortunately, Orchids nearly went bankrupt because of the dual pressure from the high cost strategy and the debt from leveraged buyout. At the moment, its raw material and production costs exceeded its profits from customers. Orchids were forced to file for bankruptcy in 1992 and 1995.Orchids' new management organization lead by the general manager, Mike Safe and chief financial officer Jim Swagerty decided to focus on core markets, where had value-seeking customers. They moved the company from California to Pryor, Oklahoma, where the utility costs were low (paper is a resource-intensive industries) and the company's recycled papers were salable. They used a low-cost strategy so that the firm's production capacity will be maximized when companies emphasize timely delivery and allow customers to clearly understand the implementation of their orders. Orchids target market is the span from Oklahoma to Atlanta.Before the reorganization,Orchids is well known for poor service and late delivery. The company did not implement the operating and reporting practices and the financial department can not provide timely and accurate information.Orchids installed a new manufacturing resource planning systems (MRP-Ⅱ) and a financial system. The two software management systems from the Marion Ohio can monitor and coordinate sales, Inventory and financial data. They can also provide the charts based daily operations for the company. Workers and all departments can directly access to the products and order information through a central server linked with the stored data through 25personal computers. Finance Department staff can also use this system to provide timely and accurate information about the operating capacity, transportation and the product usability. They can also answer the customers’ questions. Therefore, finance department staffs make use of the financial capabilities to do more about controlling and customer service. Because employees can easily access to ensure immediate and accurate information needed to order delivery. Orchids Company can keep operating costs low. This system also makes the management of Orchids in the absence of bloated bodies and the sharp reduction in the total number of case workers to run properly. Orchids started to make profit again and its organizational and technological changes made it win a place in the industry which has traditionally been monopolized by large companies.Orchids Paper used the information systems to get the lead in the competitive advantage by providing low-cost high service products. However, compared to the simply the technological leap, it is more important to maintain this competitive edge. Managers need to find ways to maintain this competitive advantage for many years. Specifically, managers need to face the following challenges:1. Comprehensive integration: although in the company different systems are designed to serve different levels and different departments, more and more companies discovery the benefits of integrated systems. Many companies are pursuing enterprise resource planning (ERP). However, the integrated system is difficult and costly for the different organizational levels and functions to exchange of information through the technology. Managers need to determine which level of information system needs to integrate and how much it costs.2. The ability to maintain the competitive advantage: the competitive advantage brought by the strategic information systems cannot sustain long enough to ensure long-term profitability. Competitors can also install the strategic information systems. Competitive advantage is not always maintained as the market is changing rapidly. Business and economic environment is changing also. Internet can make some of the company's competitive advantage disappear soon. Technology and customer expectations are changing as well. Classic strategic information systems, such as American Airlines SABRE computer reservation systems, ATM systems and City Bank Federal Express package tracking system are benefiting users because they are the first in their respective industries. But the competitors apply the corresponding systems later. Relying on information systems solely can not get lasting business advantage. Information system originally used in decision-making often becomes a survival tool (for each company in order to survive in the industry to take some measures), or information system or even inhibit the future success of organizations to make the necessary decisions.ORCHIDS Paper Company's experience shows that information systems are very important in support of the organization's goals and making the company in the leading role in competition. In this chapter, we introduce the functions of various information systems in the organization. Then,we present the issues of the company in the competition and the methods that the Information System provides a competitive advantage in three different commercial levels.2．1 The function of the major Information System in the organizationBecause of the different attention to different targets, different characteristics and different levels in the various departments in an organization, there are different kinds of information systems. Single system cannot provide organizations with all the required information. Figure 2-1 is a description of the methods of all kinds of information systems in the organization. In the chart, the organization is divided into strategic layer, management layer, knowledge layer and business layer. And then it is further translated into the various functions into areas such as sales, marketing, production, finance, accounting and human resources. Information System is set up to meet the requirements of different organizations.2.2.1 Four different information systemsThere are four different information systems which are used for different levels of the organization. They are business layer systems, knowledge-tier system, management system and strategic level system.Business layer supports managers’work through tracking the basic business activities and things of the organization. Basic operations are such as sales progress, cash store, payroll, customer credibility determination and plant logistics. On this level，the main purpose of the system is to answer normal questions, analyze the problem of the logistics and inventory number of the organization. What is Mr. William payment and what is the problem? To answer these questions, the information must be available and the information should be current and accurate. The examples of business layer of the information system: the system using ATM data to record the bank deposit, the system to record daily time that employees work in factories, etc.Knowledge level information systems support the employees who are working for the knowledge and data in the organization. Knowledge level information system is intended to help businesses find new knowledge. New knowledge will be integrated into enterprises and help companies control document things。
topic9
Three Types of Systems
¥ems ¥ Integrated systems
2
Data-driven Systems
¥ Objective: To be able to retrieve the data needed from operational systems ¥ Database back-end ¥ Integrated data sets from multiple systems ¥ User-friendly query language ¥ Simple user interface
References
¥ Arnott, D & OÕDonnell P (1994), ÔReadings in Decision Support SystemsÕ, Monash University Department of Information Systems ¥ ¥
3
Types of Model-driven Systems
¥ Spreadsheets ¥ Specialised statistical analysis software (SAS, SPSS, etc) ¥ Modelling and forecasting software (OLAP)
Jargon Overload:
Where Management meets Computing
¥ Business intelligence/knowledge management/enterprise management ¥ DSS/MIS/EIS/OLAP/ROLAP/MOLAP ¥ Data warehouse/data mart/data mining ¥ Schemas/relational data/multidimensional models/ data cubes ¥ Data cleanliness/data granularity/data populating/data mapping ¥ Drill down/scalability
- 1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。
CIS 465 -Types of Information Systems (99F)
1
Case: Frito Lay
Frito-Lay, Inc., a snack food subsidiary of Pepsi-Cola, outfitted its 10,000-person direct store-delivery sales force with handheld terminals used while calling on the 400,000 stores that sell its 100 products. Salespeople use the terminals to enter replenishment orders and record the number of “stales” removed after their 35-day shelf life. Based on this data, a printer in the truck prints an invoice handed to the store manager as part of the day’s deliveries. Salespeople hook the terminals to telephone lines to transfer each day’s data to the company’s mainframe computers in Dallas. The system saves salespeople four or five hours of paperwork per week.
CIS 465 -Types of Information Systems (99F)
2
The mainframes in Dallas consolidate the data each night as part of Frito-Lay’s internal replenishment system. Requirements for that system changed drastically in the 1980s, and Frito-Lay’s regional competitors became stronger. Frito-Lay had to be able to respond quickly to a variety of competitive challenges, ranging from price changes to totally new products. Coordination between manufacturing and sales had to be much tighter because the company needed to be able to run local promotions on Thursday for a product that would have to be available on Monday.
CIS 465 -Types of Information Systems (99F)
4
Question:
What type(s) of information systems does the case illustrate?
Debate:
The ability of large firms to build information systems like the one in the case gives them unfair advantages over small firms that lack both the staff and money to build such systems.
CIS 465 -Types of Information Systems (99F)
3
The system also used a data warehouse to provide comprehensive, up-to-date data for studying sales by any combination of product, store, and time period. In South Texas, the data from this system showed an unexpected drop in sales of Tostitos tortilla chips. Research into the cause of the drop indicated that a small competitor had launched a white corn tortilla chip. Frito-Lay developed a competitive white corn product within three months and regained market share.
CIS 465 -Types of Information Systems (99F)
5
The Frito-Lay information system supports a range of communication and decision-making functions typically associated with different types of information systems. It is a transaction processing system because it is used to enter orders from each retailer. It can be considered a management information system or executive information system because it provides information in a readily available form for management’s use. It is a decision support system because it supports decision making by helping route drivers, customers, and managers obtain needed information in a genuinely useful form.