Benjamin Khoo

TITLE:

Web-Based Decision Making Support Systems

TOPIC AREA: Management Information Systems KEYWORDS:

decision support systems, web-delivery, information technology

AUTHOR:

Benjamin Khoo, Ph.D. (lead & corresponding author) Assistant Professor Computer Information Systems Dept., College of Business Administration, California State Polytechnic University, 3801 West Temple Avenue, Pomona, CA 91768 EMAIL: [email protected] OR [email protected] TELEPHONE: (909) 869-2012 FAX: (909) 869-3248

AUTHOR:

Guisseppe Forgionne, Ph.D. Professor Information Systems Dept., University of Maryland, Baltimore County 1000 Hilltop Circle, Baltimore, MD 21250

WEB-BASED DECISION MAKING SUPPORT SYSTEMS ABSTRACT The advent of the Internet has resulted in a trend toward network centric computing. As a result, more of the computing work is delegated to the computer and the underlying systems. For many years, researchers have been working towards the development of shareable and re-usable problem-solving components to support decision-making. Web technologies provide a new means of sharing decision support functionalities and delivering decision support capabilities. This critically examines two such systems: DecisionNet and Open-DSS Protocol.

INTRODUCTION The technological explosion of the Internet in the late 1980s and early 1990s has resulted in a paradigm shift that has affected all aspects of our lives. As the world struggles to catch up with this client/server model, an emerging trend is a movement toward network centric computing. The rapid adoption by businesses of the Internet, Intranet and Extranet has pushed the fringes of information systems towards a new frontier. The advent of new programming languages such as Java (“write once, run anywhere”) and JavaScript, combined with the client-server architecture adopted by many organizations, has opened new opportunities for information systems researchers to develop distributed, network centric systems. As a result, the trend is to delegate to the computer and the underlying systems more of the computing work. In this new model, the content, communication, and computing converge on the network resulting in the network becoming THE COMPUTER. The current environment in which organizations find themselves is a highly dynamic one. This environment has created a need to respond speedily and flexibly to external changes

(Morton, 1991). This need has profoundly affected decision making and the information systems that support the process. For many years, researchers have been working towards the development of shareable and re-usable problem-solving components to support decision-making (Chandrasekaran, 1986; Walther, Eriksson & Musen, 1992; Wielinga et al., 1993). The aim is to build flexible component-based systems that are adaptable. But this has not been implemented successfully on a large-scale in cross-platform components due to a lack of standards and the enormous costs involved with the implementation. These characteristics have altered the traditional view of decision making support systems.

BACKGROUND Management is an integral function of an organization, and a principal component of management is the complex process of decision making (Keen & Scott Morton, 1978, Turban & Aronson, 2001). In Herbert Simon’s view, decision making involves intelligence, design, choice, and implementation (Simon, 1977). There is recognition of a problem or opportunity, the identification of possible causes, the development of alternative solutions, the selection among alternative causes of actions, and carrying out the chosen action. Computer based systems developed to support decision making are called decision support systems (DSS) (Morton, 1971; Keen and Scott Morton, 1978). According to Holsapple, (2001): Decision-making is a knowledge-intensive activity with knowledge as its raw materials, work-in-process, by-products, and finished goods. Computer-based DSSs employ various KM[knowledge management] techniques to represent and process knowledge of interest to decision makers, including descriptive knowledge (e.g. data,

information), procedure knowledge (e.g. algorithms), and reasoning knowledge (e.g. rules).

The DSS domain has had an illustrious history, beginning formally in the 1960s (Keen and Morton, 1978). There have been many papers written about the general state of the art in DSS and its associated technologies (see, for example, the Decision Support Systems Journal, volume 33 (2002), with articles by Powell (2001), Power (1999), Power and Karpathi (1998) and Power (1997), and others). The two most common implementations of DSS use the data-driven or the model-driven approach. The model-driven approach uses good quality models with strong analysis capabilities and a user friendly user interface to facilitate ease of interaction. In the data-driven approach, the value added to the DSS is provided by the data where the model is usually simple, computing information like averages and data distributions, and the intent is to allow the user to condense huge amounts of data into a form that is useful for decision making (Dhar and Stein, 1997). In recent years there has been an evolution in the type of information sources used in DSS from an emphasis on stored data and data analysis to an increased reliance on decision models. Research in decision support systems also has highlighted the importance of technology to the decision making process (Forgionne, 1991a; Kendall, 1999; Zahedi, 1991).

WEB-BASED SYSTEMS

Of the technologies that influenced the development of DSS, internetworking, or web technology, is arguably the most prevalent one today. Web technologies provide a new means of sharing decision support functionalities and delivering decision support capabilities. (Power, 2000a) and (Power, 2000b) suggested some frameworks for organizing DSS on the web. Web technologies have also made it possible to implement DSS using the other approaches, apart from the data-driven and model-driven approaches, like the communication-driven, knowledge-driven and document-driven approaches. The communication-driven approach utilizes web communication technologies to assist decision makers who might be at different locations, at different times, to collaborate and resolve problems. The knowledge-driven approach utilizes web technologies to recommend and deliver recommended actions to a broad spectrum of decision makers. The document-driven approach utilizes web technologies to integrate the storage, retrieval and processing of different types of documents for decision makers to read and analyze (Bhargava and Power, 2001). Developers have started to develop web enabled DSS as services which can be accessed from anywhere through an Internet connection. The services can combine multiple components from different sources to deliver application solutions. Papers by (Cohen et al., 2001) and (Czyzyk et al., 1997) described some of the services that were enabled by web technologies. (Bhargava and Krishnan, 1998) classified web technologies into 3 main categories: enabling server-side computation (e.g. Java Server Pages, Active Server Pages, Java applications, etc.), enabling client-side computation (e.g. Java applets,

client-side scripting languages, etc.) and enabling a distributed implementation and deployment of DSS components (e.g. CORBA, Java RMI, Java Beans, etc.) Web technology can be applied on enterprise intranets, as well as on the Internet. Since corporate decision makers are not willing to cede control of corporate data and models to internet-based DSS, an enterprise-wide knowledge portal (corporate intranet-based DSS) has been developed. The technologies that can be utilized to enable intranet-based DSS have not been fully explored. Further research in this direction is needed to fully extend the capabilities of corporate intranet-based DSS. Although many DSSs have been developed and implemented over the last twenty years, few are readily available to everyone, anywhere and at anytime. Some issues faced by users of decision technologies (Bhargava & Norris, 1996) are: Awareness: Users may not be aware of relevant technologies. Accessibility: Users may not have access to beneficial technologies. Compatibility: Most technologies require specific hardware and software configurations. Applicability: Due to both the complexity - expertise, effort, and cost - of developing decision technologies and the limited market-base, there is little motivation for providers to create easily adaptable models. Interoperability: Many decision problems require a combination of technologies to provide a satisfactory solution. Some problems faced by providers of decision technologies (Bhargava & Norris, 1996) are: Advertisement (awareness & accessibility): As new decision technologies are developed, providers need to attract users. Currently, it is difficult for specialized software providers to cost-effectively reach consumers. Heterogeneity (compatibility): Even in niche markets, there is heterogeneity of computational platforms. For providers looking for market share, this chracteristic creates the expense of supporting the technology on a variety of platforms.

Version Management (compatibility): Often a working version of a product is rendered useless due to a change in, say, operating system software. Even in the absence of shifts in the user platform, a variant of this problem is encountered, as there is a need to upgrade and maintain software over time. Customization (applicability and inter operability): The cost of producing and customizing decision technology software using a traditional software distribution strategy is high due to the small and specialized nature of the market. This problem is exacerbated by the need to offer coordinated or integrated inter operable solutions. As a result, few systems had been developed to provide decision support on demand.

DECISIONNET DecisionNet (Bhargava, Krishnan and Muller, 1995; Bhargava, Krishnan and Muller, 1996) is a web-based marketplace for decision support technologies. It is a broker-based system that facilitates services between consumers (users of DSS) and providers (providers of DSS services). Its basic modus operandi is that all providers have to submit their DSS for inclusion in the DecisionNet system and all customers have to register to use DecisionNet. Once registered, consumers can access the DSS on the system and run the specific DSS that is needed remotely. In this way, consumers do not have to download any software; they can utilize the DecisionNet system hardware and services. The key features of DecisionNet include (Bhargava, Krishnan and Muller, 1996): DecisionNet features all types of decision technologies from data sets to modeling environments, placing the niche data-set provider on equal footing with those that own high-end, expensive computational platforms and modeling environments. Providers are given access to an intelligent registration agent, which leads them through a series of steps resulting in both a listing for DecisionNet yellow pages and in the automated creation of a web-based user interface to the technology.

Consumers in DecisionNet can use the services of an intelligent agent to cobble together a solution using available technologies. Providers are not required to supply their technologies on a platform owned by DecisionNet. After registering the appropriate protocol to invoke their technology (e.g., anonymous telnet or the POST method of the http protocol), providers maintain their own servers, leveraging the distributed nature of the web and permitting scalability. Providers of DSS to DecisionNet maintain their own technologies. DecisionNet acts as a broker to guide the consumer in the search, selection and execution of these technologies. The operation of DecisionNet is based on the notion of "pay-per-use" where the decision technologies available are provided as a service rather than as a product. There are a number of limitations to the DecisionNet implementation (Gregg and Goul, 1999; Gregg, et al., 2002). Apparently, consumers can have problems accessing the web site because of firewall configurations and other security issues. In addition, if either the DecisionNet or provider's link is down or poorly maintained, end users would have unreliable access to the decision support tools. The accessibility issue has not been resolved. If the consumer is able to access the system, the user can choose options from the menu and receive a listing of the technologies available. This listing is visible on the browser but it cannot be saved. According to the DecisionNet site all potential consumers of DecisionNet need is a forms-capable WWW browser. It indicated that most interaction with technologies could be achieved via HTML fill-out forms. However, for interactions involving larger data sets, users may also need to have FTP or SMTP client software. Users are also dependent on the number of providers who submit their DSS products; apparently there are few or none available. This is understandable from an economic perspective. DSS developer enterprises would not want

to be dependent on a single channel such as DecisionNet to market their product. Also, such a channel is not within their control; there is no competitive advantage to the enterprise.

OPEN-DSS PROTOCOL (Goul, et al., 1997) has suggested another web-based DSS system called Open-DSS Protocol. The Open-DSS Protocol is a general protocol that provides facilitated access to DSSs utilizing the existing Internet application layer protocols, HyperText Transfer Protocol (HTTP) and HyperText Markup Language (HTML). The first layer in the Open-DSS protocol is the Metainformation Layer. It indicates that the Web site contains a DSS and includes all of the information necessary to completely explain the DSS. The second layer is the Transaction Processing Layer. This Layer is responsible for any transactions that are necessary before the software will be made available to the client. The Meta-Information Layer takes care of processing meta-information relating to the DSS offered at web sites. Information about objects transferred over the Internet ("meta-information") is transferred in its HTTP headers. The Open-DSS protocol requires the encoding of sets of specialized headers to provide basic information about the DSS to special automated intelligent search agents. These special search agents will crawl the WWW requesting entity-header information only (using the HEAD command) to determine if the WWW site contains a DSS. The special headers will not affect other search agents since, by convention, unrecognized HTTP headers and parameters are ignored. The header information provided by DSS providers must be in a consistent format so that the automated DSS search agents can index them correctly. The basic information necessary for DSS headers includes

the content-type (DSS), a list of keywords, a description of the DSS, the functionality of the DSS being offered, the user-site requirements and other information necessary to evaluate the DSS. The type of information that should be included in the metainformation for the DSS's functionality includes the problem domain of the analysis, the solution options, the inputs, the outputs and assumptions made. The information on the resources to be provided by the user should include information on the hardware requirements (for example, computing platform), software requirements (for example, operating system or application needs), and any specific user skills required to use the DSS. Finally, the metainformation header must contain all other information necessary to purchase and download the DSS. This would include information on the DSS's cost, its references, related DSSs, and vendor information. The Transaction Processing Layer is envisioned to be open such that individual DSS developers can either create their own transaction processing software or purchase any commercially available product. The functionalities of the Transaction Processing layer will include user registration, access control, profiling, secure credit card transaction processing and billing. User registration could include login and registration templates, which DSS providers could use to gather data about customers. When registering, users can be asked to enter information about interests and occupation along with their name, phone number and e-mail address. The intent of this additional information is mainly customer data for DSS developer enterprises. To cater to business transactions for utilizing the DSS, some type of billing services in the transaction layer would allow payment capture and invoicing, credit card processing and activity tracking.

It should be noted that Open-DSS Protocol is currently a conceptualization. For the Open-DSS Protocol to be viable, it had to be implemented across the WWW. The DSS developer enterprises or vendors had to agree to the additional standardized encoding on the HTTP headers. In addition, specialized search agents had to be developed. This scheme also have some unresolved issues when viewed from an economic perspective. It suffers from similar weaknesses as DecisionNet. Currently, vendors are selling products with what is available on the Internet; unless there is some additional motivation to get onto the Open-DSS Protocol bandwagon, it is likely to remain just a conceptualization.

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