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A PROPOSED GIS-BASED DECISION MAKING FRAMEWORK FOR TOURISM DEVELOPMENT SITES SELECTION

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Building a new tourism facility is a critical decision made by private and public owners. Determining facilities locations is critical to the success and failure of such investments. The selection of a tourism development site involves a complex array of decision factors involving economic, social, technical, and environmental issues. In the process of finding the optimum location that meet desired conditions the analyst is challenged by the tedious manipulation of spatial data and the management of multiple decision-making criteria. Geographic information systems (GIS), Multicriteria Decision Making techniques (MCDM), and Expert Systems (ES) are the most common tools employed to solve sitting problems. However, each suffers from serious shortcomings and could not be used alone to reach an optimum solution. This paper presents a new decision making framework in which ES, GIS and MCDM techniques are integrated systematically to facilitate decision-making regarding selection of suitable sites for building tourism facilities.
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The International Arab Conference on Information Technology (ACIT) 1
A PROPOSED GIS-BASED DECISION MAKING FRAMEWORK FOR TOURISM
DEVELOPMENT SITES SELECTION
MOHAMMED A. AL-AMRI and KHALID A. ELDRANDALY*
King Abdulaziz University, Jeddah, KSA
ABSTRACT
Building a new tourism facility is a critical decision made by private and public owners. Determining facilities locations is
critical to the success and failure of such investments. The selection of a tourism development site involves a complex array of
decision factors involving economic, social, technical, and environmental issues. In the process of finding the optimum
location that meet desired conditions the analyst is challenged by the tedious manipulation of spatial data and the
management of multiple decision-making criteria. Geographic information systems (GIS), Multicriteria Decision Making
techniques (MCDM), and Expert Systems (ES) are the most common tools employed to solve sitting problems. However, each
suffers from serious shortcomings and could not be used alone to reach an optimum solution. This paper presents a new
decision making framework in which ES, GIS and MCDM techniques are integrated systematically to facilitate decision-
making regarding selection of suitable sites for building tourism facilities.
Keywords: Tourism Site Selection, GIS, ES, MCDM
1. INTRODUCTION*
Building a new tourism facility is a major, long-term
investment for owners and investors. Site selection of a
capital project is a critical decision made by
owners/investors that significantly affects their profit
and loss. Decisions regarding the locations of tourism
facilities would influence the life-style of a community.
As such, tourism development site location analysis is
big business, whether measured in terms of amounts
invested, decision-makers involved, size of
communities affected, and the prosperity of the area
influenced.
The goal in a site selection exercise is to find the
best location with desired conditions that satisfy
predetermined selection criteria [8]. The process of
selection could involve a large number of candidate
sites [30, 36]. The selection process attempts to
optimize a number of objectives in determining the
suitability of a particular site for a defined facility. Such
optimization often involves a multitude of factors,
which are sometime contradicting.
A number of tools have been used to determine the
proper site for a capital improvement facility. These
tools include Expert Systems (ES), geographic
information systems (GIS), and Multi-criteria decision-
making (MCDM) techniques. Although these tools
have played an important role in solving site selection
problems, each tool has its own limitations. The need
for combining the strengths of these techniques has
prompted researchers to seek integration of, ES, GIS
and MCDM [14]. There is now a well-established body
of literature on integrating ES, GIS and MCE
techniques for solving site selection problems (see for
example [5, 10, 12, 13, 21, 22, 26, 34, 38]. However,
*Corresponding Author E-Mail: keldrandaly@kau.edi.sa
according to the best of our knowledge, most of these
papers don’t cover the topic of tourism development
site selection.
This paper presents a new decision making
framework in which these three tools are combined in
a manner so that the shortcoming of one tool is
complemented by the strength of another. The
proposed decision making framework assists the
decision maker by providing an advisory expert
system that recommends the proper site selection
criteria (e.g., physical, environmental, geographical,
non-spatial criteria, etc.). The GIS is used to perform
the spatial data analysis necessary to identify possible
candidate sites. The Analytic Hierarchy Process
(AHP), a MCDM method, is utilized to select the most
suitable sites considering the analyst’s prioritization of
the different criteria. Since the topic of the paper is
rather specialized, a brief description of the site
selection process, characteristics and tools are
described first.
2. SITE SELECTION PROCESS
The process of tourism development site selection
begins with the recognition of an existing or projected
need to meet new or-growing markets. This
recognition triggers a series of actions that starts with
screening of geographic areas of specific interest.
Sites that satisfy the screening criteria are subjected to
a more detailed evaluation and are compared as
possible alternative sites for the proposed facility.
Usually, the screening criteria would include
economics, social, and environmental
measures/factors. In the past, the site most suited for
the recognized need was selected more on purely
economical and technical criteria. Today, a higher
degree of sophistication in the selection process is
expected and the number of factors one must be
2 The International Arab Conference on Information Technology (ACIT)
contented with has multiplied as social and
environmental aspects have received more emphasis in
the process and are enforced by legislations and
regulations. This has significantly expanded the list of
decision factors that must be considered in determining
potential tourism facility location [4, 23, 35, 36, 40].
3. SITE SELECTION CHARACTERISTICS
In today’s society, site selection problems are
characterized by their multi- objectives and numerous
stakeholders. To appreciate the complexity of the
selection process, a brief description of the factors that
generally characterize the problem and affect final
selection is provided below [23, 40]:
Numerous possible sites -- Within a region of interest,
there could be tens or even hundreds of potential sites
that could be chosen for the facility.
Multiple objectives -- It is fairly common to find
contradiction between the multiple objectives for a
sitting problem. For instance, the objective of keeping
minimum capital investment may contradict with the
objective of keeping a long-term safe environment.
Intangible objectives -- Many objectives lack means
for quantitative measurements. Examples of those are
the aesthetic deterioration of the view of a mountain
scene as a result of the installation of transmission
towers/lines, the social disruption felt by a community
as a result of the expected rapid influx of workers
during construction, and similar issues.
Diversity of interest groups -- Frequently,
owners/investors decisions are impacted by several
public groups in addition to their own organizations.
These public groups may include consumers, local
citizens, environmentalists, heritage committees and
similar groups. Within an owner’s organization the
management, shareholders, and employees may hold
different positions regarding the selected site.
Impact Assessment -- Placing a value on the impact of
each objective could be problematic. It is not enough to
state that there would/wouldn’t be some impact. A
value (number or quantity) is needed to support the
comparison process.
Impact timing -- The impacts identified by a sitting
study may not all occur at the same time and may/may
not continue over the lifetime of the project.
Impact uncertainties -- It is practically impossible to
accurately forecast all possible impacts of all factors
affecting the site selection for a facility. There will
always be uncertainties regarding environmental
outcome, actual costs, accidents, and similar issues.
Delays -- Licensing and construction issues are
examples of common unpredictable delays that may
significantly impact the economic viability of the
project.
Operation reliability -- Uncontrollable and
unpredictable natural phenomena such as storms,
floods, quacks and similar phenomena can impact site
suitability and add to the process uncertainty.
Equity -- Determining equity and fairness among all
interest groups could be a difficult task that involves
complex value judgments.
Stakeholders’ risk attitudes -- Determination and
compilation of the stakeholders’ risk attitudes (utility
functions) is important to the proper site selection.
Uncertainties in government decisions -- laws and
regulations enforced by federal and state governments
can have a great influence on the relative desirability
over time of various sites for a proposed facility.
4. SITE SELECTION TOOLS
Geographic information systems (GIS), Multi-criteria
decision making (MCDM), and Expert Systems (ES)
techniques have been used in solving site selection
problems for the last three decades. However, each of
these techniques has its own limitations in dealing
with siting problems. In the following sections, a brief
introduction to ES, GIS and MCDM and their
limitations in dealing with the sitting problem is
provided.
4.1. EXPERT SYSTEMS
ES have achieved considerable success in many fields
in recent years. An Expert system is an intelligent
computer program that uses knowledge and inference
procedures to solve problems that require significant
human expertise for their solutions. An expert system
generally consists of a knowledgebase, inference
engine, working memory, user interface, and
knowledge acquisition mechanism. An expert system
is called a system rather than a program because it
contains both a problem solving component and a
support component. The support component is the part
in the system that assists the user in interacting with
the problem solving component and provides aids
such as debugging utilities to test/evaluate the code,
editing utilities to modify the knowledgebase, and
graphic utilities to facilitate user’s input [11, 17, 39].
Many expert systems have attempted to solve various
site selection problems that are heavily dependent on
human judgment and experience. Examples of such
attempts were reported by Arentz et al [2], Witlox and
Timmermans [41], Arentz et al [1], Han and Kim [16],
Rouhani and Kangari [33], Findikak [15], Suh et al
[37].
Expert systems, however, lack the necessary
mechanism to derive solutions based on spatial
knowledge of different sites. They use symbolic
knowledge to construct human understanding of
problems in the area of site selection and evaluation,
which is not well suited for representing spatial data.
Unfortunately, current expert systems can’t handle
spatial knowledge, as they do not have an appropriate
A Proposed GIS-Based Decision Making Framework for Tourism Development Sites Selection 3
method to encode and represent the spatial knowledge.
Furthermore, they lack essential capabilities such as
buffering (i.e., defining a zone of a specified distance
around features) and overlay (i.e., integration of
different data layers), which are crucial to spatial data
analysis [14, 19, 44].
4.2. GEOGRAPHIC INFORMATION SYSTEMS
GIS is a relatively new branch of information
technology and the term GIS did not appear until the
early 1960s [25]. GIS is a computer-based information
system that enables capture, modeling, storage,
retrieval, sharing, manipulation, analysis, and
presentation of geographically referenced data [42].GIS
have often been used to identify suitable areas for land
developments and the use of GIS in sitting analysis
started in the late 1970s [6, 9, 20, 31, 32, 43]. The
success of GIS in sitting problems was attributed to its
ability to perform deterministic overlay and buffer
operations.
GIS however, while possessing ideal capabilities for
performing spatial searches based on nominally
mapped criteria, are of limited use when multiple
criteria and conflicting objectives are considered in the
analysis [7]. In addition, GIS have very limited
capabilities for integrating geographical information
with the decision maker’s values and preferences and
hence are of limited use for decision support [27].
4.3. MULTI-CRITERIA DECISION-MAKING
TECHNIQUES
MCDM Techniques were designed to analyze decision
problems, generate useful alternative solutions, and to
evaluate the alternatives based on a decision maker’s
values and preferences. The general objective of these
methods is to assist the decision-maker in selecting the
best alternative from the number of feasible alternatives
under the presence of multiple choice criteria and
diverse criterion priorities [18, 29]. MCDM techniques
have been used to solve various site selection problems
[3, 24].
These techniques, however, assume homogeneity
within the study area, which is unrealistic in many
spatial decision making situations such as site selection
problems. Malczewski [27] suggested that there is a
need for an explicit representation of geographical
dimension in MCDM techniques. The combination of
GIS and MCDM capabilities could effectively solve
this problem.
5. PROPOSED DECISION MAKING
FRAMEWORK
A new decision making framework for tourism site-
selection is proposed. The proposed framework
integrates the capabilities of ES, GIS and MCDM
(AHP). Recommendations regarding the design of a
good sitting methodology were observed [23, 40] in
the design of the proposed framework. These
recommendations include: a) identification of
facility’s goals, b) providing quality analysis (i.e.,
logically sound, defensible, and useful for decision-
making) c) offering practical methodology (i.e., ability
to conduct studies in the real environment with
available methods and procedures provided at a
reasonable cost and time), and d) documenting how
local conditions are analyzed. Figure 1 depicts the
three phases of the proposed framework (i.e., defining
siting criteria, preparing standardized criterion maps,
multicriteria evaluation) and their procedural steps as
explained below:
5.1. DEFINING SITING CRITERIA PHASE
According to the type of the proposed tourism facility,
an expert system is used to define the recommended
siting criteria (physical, environmental, geographical,
engineering criteria, etc.). The decision maker has the
option of accepting or modifying these recommended
criteria.
5.2. PREPARING STANDARDIZED
CRITERION MAPS
After defining the siting criteria, the analyst prepares
the criterion maps based on the predefined siting
criteria. Central to spatial multicriteria decision
making is the fact that an attribute can be represented
in a GIS database as an attribute (criterion) map layer.
A criterion map represents the spatial distribution of
an attribute that measures the degree to which its
associated objective is achieved. Given a variety of
scales on which each criterion can be measured,
multicriteria evaluation requires that values contained
in the various criterion map layers be transformed to
comparable units (standardized to a common scale).
The procedure for generating criterion maps is based
on different GIS functions. Detailed descriptions of
standardization approaches are reported elsewhere
[27].
5.3. MULTICRITERIA EVALUATION
After preparing the standardized criterion maps,
Analytic Hierarchy Process (AHP), one of the most
common used MCDM techniques, is used for ranking
the alternatives sites according to the decision maker’s
preferences. AHP is a method that allows the
consideration of both objective and subjective factors
in ranking alternatives. Since its introduction in the
mid 1970s by Thomas Saaty, AHP has been applied in
a wide variety of practical applications in various
fields including siting problems. AHP is based on
three principles: decomposition, comparative
judgment, and synthesis of priorities. The
decomposition principle requires that the decision
4 The International Arab Conference on Information Technology (ACIT)
problem be decomposed into a hierarchy that captures
the essential elements of the problem. The principle of
comparative judgment requires assessment of pairwise
comparisons of the elements within a given level of the
hierarchical structure, with respect to their parent in the
next-higher level. The synthesis principle takes each of
the derived ratio-scale local priorities in the various
levels of the hierarchy and constructs a composite
(global) set of priorities for the elements at the lowest
level of the hierarchy (i.e., alternatives). Additional
description on AHP can be found elsewhere [18, 27,
29].
Figure 1. Proposed Decision Making Framework
To implement the proposed spatial decision making
framework, a prototype intelligent GIS-based spatial
decision support system (Tourism Site Selection
Advisory System- TSSAS) is developed using
Microsoft® Component Object Model (COM). The
COM is a standard that enhances software
interoperability by allowing different software
components, possibly written in different programming
languages, to communicate directly [28]. A number of
COM-compliant software packages are required to
develop the proposed system.. The ArcGIS ® 9.3 is
used to manage the spatial data and to conduct the
required spatial analysis operations
(http://www.esri.com). The Visual Rule Studio® is
used to develop the expert systems component
(http://www.RuleMachines.com). Visual Studio 2005
(C# Programming Language) and ArcObjects libraries
are used to develop the MCDM module (AHP) as an
extension to ArcGIS.
6. CONCLUSIONS
Tourism development site selection process has become
increasingly complex because of the plethora of
technical, non-technical (i.e., environmental laws and
regulations), and the increasing public awareness and
involvement. ES, GIS and MCDM are very efficient
tools for solving sitting problem. However, each of
these tools has its limitations and drawbacks in
solving such problems. The integration of these
techniques eliminated these limitations and provided
the decision maker with an innovative approach to
sitting problem.
This paper proposed a new decision making
framework for solving tourism development site
selection. The proposed framework integrates the
capabilities of ES, GIS and MCDM (AHP). The
proposed decision making framework assists the
decision maker by providing an advisory expert
system that recommends the proper selection criteria
(e.g., physical, environmental, geographical, non-
spatial criteria, etc.) based on the type of the tourism
facility. The GIS is used to perform the spatial data
analysis necessary to identify possible candidate sites.
AHP is utilized to select the most suitable sites
considering the analyst’s prioritization of the different
criteria.
ACKNOWLEDGMENTS
This research was supported by the Research Grants
Program of King Abdulaziz University, Jeddah, Saudi
Arabia.
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This special project aims to study conceptual framework of Multi-Criteria Decision Making methods (MCDM). Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were applied to select the proper service provider as a container depot for shipping company. The objective of case study is to meet shipping company’s requirement meanwhile customers’ satisfaction is a must. In addition, writer also focuses on important spatial criterias and weight of evaluated criterias in order to be outline of improvement or future expansion for other service providers. Initial step of selection, list of 45 service providers were considered term of service agreement and screened out by shipping company’s top management. Geographic Information System (GIS; computer program), then were input spatial criterias and analyzed efficient service providers as to be potential alternatives for MCDM application afterwards.
Article
Many real-world decision problems have multiple objectives. For example, when choosing a medical treatment plan, we want to maximize the efficacy of the treatment, but also minimize the side effects. These objectives typically conflict, e.g., we can often increase the efficacy of the treatment, but at the cost of more severe side effects. In this book, we outline how to deal with multiple objectives in decision-theoretic planning and reinforcement learning algorithms. To illustrate this, we employ the popular problem classes of multi-objective Markov decision processes (MOMDPs) and multi-objective coordination graphs (MO-CoGs). First, we discuss different use cases for multi-objective decision making, and why they often necessitate explicitly multi-objective algorithms. We advocate a utility-based approach to multi-objective decision making, i.e., that what constitutes an optimal solution to a multi-objective decision problem should be derived from the available information about user utility. We show how different assumptions about user utility and what types of policies are allowed lead to different solution concepts, which we outline in a taxonomy of multi-objective decision problems. Second, we show how to create new methods for multi-objective decision making using existing single-objective methods as a basis. Focusing on planning, we describe two ways to creating multi-objective algorithms: in the inner loop approach, the inner workings of a single-objective method are adapted to work with multi-objective solution concepts; in the outer loop approach, a wrapper is created around a single-objective method that solves the multi-objective problem as a series of single-objective problems. After discussing the creation of such methods for the planning setting, we discuss how these approaches apply to the learning setting. Next, we discuss three promising application domains for multi-objective decision making algorithms: energy, health, and infrastructure and transportation. Finally, we conclude by outlining important open problems and promising future directions. Table of Contents: Preface / Acknowledgments / Table of Abbreviations / Introduction / Multi-Objective Decision Problems / Taxonomy / Inner Loop Planning / Outer Loop Planning / Learning / Applications / Conclusions and Future Work / Bibliography / Authors' Biographies http://www.morganclaypool.com/doi/abs/10.2200/S00765ED1V01Y201704AIM034
Chapter
This chapter discusses the methodologies for siting energy facilities. The dual purposes of a particular siting study are to help find the best available site, and to provide a rationale and documentation for that decision. These are obviously different from the purposes of a siting methodology. A siting methodology should provide a framework for achieving the purposes of siting. Hence, the methodology is in some sense a means to aid in achieving the end purposes of particular siting studies. The chapter discusses the requirements, that is, desired properties, for such a methodology. This is intended to clarify the meaning of “provide a framework for achieving the purposes of siting.” The chapter presents the current siting methodologies and procedures. The purpose is to outline the conceptual approach used in these methodologies and to provide a procedural overview of their implementation. The chapter also discusses their shortcomings with respect to the requirements. It presents an overview of the decision analysis siting procedure and discusses the concept of value-free analyses.
Book
This book provides a straight forward, nontechnical, visual shortcut to mastery of GIS fundamentals. The book is ideal for both students and professionals new to GIS, while serving as a quick reference to more experienced practitioners. Topics and features of the book include: GIS in the information age; basic functions of GIS; data manipulation; raster and vector for nontechnicians; understanding topology's flexibility' basic and advanced analysis; site suitability and modelling; data conversion.
Article
This study describes and explains the concepts, materials, and methods designed to make community industrial development programs more effective. It attempts to reconcile the three different--and often conflicting--interest groups involved: the industrial land user, represented by the manufacturer seraching for a location; the landowner, represented by the industrial or economic developer; and the community, represented by the planner and other government officials. Originally published in 1980. A UNC Press Enduring Edition -- UNC Press Enduring Editions use the latest in digital technology to make available again books from our distinguished backlist that were previously out of print. These editions are published unaltered from the original, and are presented in affordable paperback formats, bringing readers both historical and cultural value.
Article
PRELIMINARIES. Geographical Data, Information, and Decision Making. Introduction to GIS. Introduction to Multicriteria Decision Analysis. SPATIAL MULTICRITERIA DECISION ANALYSIS. Evaluation Criteria. Decision Alternatives and Constraints. Criterion Weighing. Decision Rules. Sensitivity Analysis. MULTICRITERIA-SPATIAL DECISION SUPPORT SYSTEMS. Spatial Decision Support Systems. MC-SDSS: Case Studies. Glossary. Selected Bibliography. Indexes.
Article
A network can model many real systems like roads, water bodies, and contours. On the area of GIS analysis, networking has become a very useful tool. Nowadays, networks from the infrastructure of the modern world commonly occur through definable network systems: transportation and distribution of goods and services, communication, delivery of resources and energy, among others. An exercise on site selection and evaluation using the tools of Geographic Information System (GIS) is presented herein. Solution to a typical problem of regional and national governments, namely to locate potential and evaluate existing sites, is hereby given utilizing the GIS tools. Geographic and network analyses were made using Arc/Info version 7. In the geographic analysis, selection of potential sites was made based on a set of criteria -accessibility, proximity to certain natural or manmade area, among other limitations as needed. The network analysis provided answers to questions on the suitability of the selected sites and who can access the sites within a specified time or distance. Using the criteria, GIS processes such as buffering, union, erase, dissolve, and intersect narrowed down the number of possible sites. Results of the geographic and network analyses were then ranked accordingly.
Article
This paper describes an algorithm for spatial search, which is used in an expert system for site selection. The algorithm, named ProfMat, is able to find the best site in the area of interest even when the number of possible sites is large and many decision criteria are involved. Compared to commonly used search procedures, ProfMat improves the efficiency of spatial search in two ways. First, the best site is identified through an iterative rather than a linear process of selection and evaluation of optional sites. Second, an area is searched by narrowing down the focus to increasingly smaller areas and, thus, sites are evaluated as much as possible groupwise. The ProfMat procedure is illustrated by analyzing the problem of retail site selection. A comparison with alternative search procedures shows that ProfMat considerably reduces the evaluation costs needed to find the best site. The implementation of the algorithm in an expert system shows how ProfMat can be used in combination with specialist's knowledge to solve site-selection problems. The efficiency of the procedure allows considering large sets of optional sites, so that it may improve the quality of the outcome.
Conference Paper
Site selection is a critical decision making element for a wide range of economic activities, from land use planning to residential location selection by individuals. Typically, site selection involves two phases. First, a small number of alternatives among all possible sites are identified for further evaluation. Then these selected alternatives are examined in depth to find the optimal site. Because of the effort required for a thorough evaluation of each site, the number of sites included in the second stage is, by necessity, small. Therefore, the first phase of the site selection process is very important because if, for example, the “best” available site is not included in the set of alternatives selected for thorough study, then this site can never be selected as the optimal site. In large scale planning the first phase involves reconnaissance and prefeasibility studies. At the individual level, it may involve consultation with a specialist.
Conference Paper
Explains the concept and development of site selection and analysis system. The Expert System for Site Analysis and Selection (ESSAS) is a prototype system with 240 decision rules, and is designed to solve a portion of the site selection problem. The system was developed to aid master planners for the Army who are responsible for planning future building projects at military bases. To incorporate intuitive judgments into the site selection process, an expert system approach seems appropriate. Information from regulations, field manuals, design guides and interviews with expert master planners was combined into the final ESSAS system. -from Editors
Article
Regulations and public opposition can make siting municipal solid waste landfills difficult. In this paper, spatial-AHP is presented, a method that identifies and ranks potential landfill areas for preliminary site assessment. Spatial-AHP takes into account regulatory restrictions, area attributes, and site assessment criteria provided by experts and/or users. The method uses an analytic environment provided by geographic information systems (GIS) and a decision-making method provided by the analytic hierarchy process (AHP). The GIS is used to manipulate and present spatial data. The AHP is used to rank potential landfill areas based on a wide variety of criteria. Spatial-AHP is demonstrated by applying it to a landfill site selection study in Cleveland County, Oklahoma. The paper also analyzes the effects of varying the relative importance. of various siting criteria, landfill size, and location restriction severity.