Stair Wear Analysis Keywords

Stone is a symbol of steadfast permanence, and carved rock is used as a building material
because of its ability to resist wear. Despite its durability, even stone is not impervious to
wear. One of the few things more resilient is the persistence of people.

The stone and other materials used to create steps are subject to constant, long-term wear, and
the wear can be uneven. For example, extremely old temples and churches may have stairs in
which the center of the steps has been worn down more than their edges, and the treads no
longer have a level top but can appear to be bowed. Due to the nature of such structures, the
buildings tend to have been inhabited by people over a very long period, but the presence of
people at a particular site often predates the construction of buildings. This can make it
difficult to accurately determine the date a structure was constructed. The situation is further
complicated when construction on a structure occurs over a very long time, renovations have
been made, and new parts to the structure have been added over time.
Your team is asked to provide guidance on what information archaeologists can determine
from a set of worn stairs. The stairs may be constructed from various materials, for example
stone or wood. Also, an estimate of when a set of stairs was constructed may be available,
however, it may be difficult to get a precise time. It may not be clear from the historical
records which set of stairs in a structure was constructed in each time period.
In addition to age, an archaeologist may also be interested in determining the traffic patterns
associated with how a stairwell was used. For example, were people moving up as well as
down the stairs at the same time or was a predominant direction used at any given time? An
archaeologist may also want to determine how often the stair well was used. For example, did
a large number of people use it over a short period or did a few people use it over a very long
period?
Your team is asked to develop a model that can determine what basic conclusions can be
drawn given a set of stairs. Your model should provide some basic predictions given the
patterns of wear on a particular set of stairs:
• How often were the stairs used?
• Was a certain direction of travel favored by the people using the stairs?
• How many people used the stairs simultaneously? (For example, did pairs of people
climb the stairs side-by-side or did they travel single file?)

You can assume that an archaeologist has access to the structure in question and can obtain
whatever measurement your team believes is important. The measurements must be made in
a way that is non-destructive, the cost must be relatively low, and the measurements can be
taken by a small team of people with minimal tools. You should make clear what
measurements are required.
There are other questions that may be more difficult to address. Assuming an estimate of the
age exists, the way the stairwell was used, and an estimate on the daily patterns of life in the
structure are available, determine what guidance can be provided to the following questions:
• Is the wear consistent with the information available?
• What is the age of the stairwell and how reliable is the estimate?
• What repairs or renovations have been conducted?
• Can the source of the material be determined? For example, if stone is used is the
wear consistent with materials from a quarry the archaeologist believes is the original
source or if wood was used is the wear consistent with the age and type of trees that
are assumed to be used?
• What information can be determined with respect to the numbers of people using the
stairs in a typical day and were there large numbers of people using the stairs over a
short time or a small number of people over a longer time?

你是一名知名的考古学家和数据学家，现在你的团队致力于解决以上提到的问题，请你给出几个关键词供相关文献的搜索

Juneau, Alaska, USA with a population of about 30,000 residents, set a record in 2023 with 1.6
million cruise passengers, hosting as many as seven large cruise ships on the busiest days, with
upwards of around 20,000 visitors.
[1] While these tourists bring in substantial revenue for the
city, on the order of $375 million,
[2] they also bring issues related to overcrowding that have the
city working to limit the number of guests. Ironically, Mendenhall Glacier, one of the premier
attractions in Juneau, has been receding, primarily due to warming temperatures caused, in part,
by overtourism. The glacier has receded the equivalent of eight football fields since 2007,
leading many locals to worry that the tourists and associated revenue will eventually disappear
with the glacier.
[3] Fortunately, Juneau has other attractions, including whale watching and rain
forests, and can maintain their status as a tourist destination, provided they can develop and enact
a plan for sustainable tourism.
Recent reports[4] have highlighted the hidden costs of tourism and the growing need to account
for and manage these costs to protect natural and cultural resources and build a sustainable
tourism industry on which numerous communities around the world depend. These hidden costs
include pressure on local infrastructure including drinking water supplies, waste management,
and an overall increased carbon footprint in tourist destinations, many of which lie in
environmentally sensitive regions. Local populations are also under pressure due to housing
supplies and costs, overcrowding, and rowdy tourists. Various measures have been enacted to
attempt to ease the burden, including increased hotel taxes, visitor fees, caps on the number of
daily visitors, and restrictions on alcohol sales and consumption. Additional revenue from taxes
have been used to support conservation, make improvements in infrastructure, and develop
community programs. While many locals that depend on tourism are concerned that additional
fees might drive tourists away and would rather see the numbers, and their businesses, grow,
many other locals are becoming disgruntled and either leaving or protesting against tourists.
• Build a model for a sustainable tourism industry in Juneau, Alaska. You may want to
consider factors such as the number of visitors, overall revenue, and measures enacted to
stabilize tourism. State clearly which factors you are optimizing, and which factors serve
as constraints. Include a plan for expenditures from any additional revenue and show how
these expenditures feed back into your model to promote sustainable tourism. Include a
sensitivity analysis and discuss which factors are most important.

假设你是一位资深数据科学家与数学家，请你思考：这在数学建模中是一个什么类型的问题（预测，评价，优化等）？你对这个可持续旅游业模型（ a model for a sustainable tourism industry），有什么思考与思路？

Juneau, Alaska, USA with a population of about 30,000 residents, set a record in 2023 with 1.6
million cruise passengers, hosting as many as seven large cruise ships on the busiest days, with
upwards of around 20,000 visitors.
[1] While these tourists bring in substantial revenue for the
city, on the order of $375 million,
[2] they also bring issues related to overcrowding that have the
city working to limit the number of guests. Ironically, Mendenhall Glacier, one of the premier
attractions in Juneau, has been receding, primarily due to warming temperatures caused, in part,
by overtourism. The glacier has receded the equivalent of eight football fields since 2007,
leading many locals to worry that the tourists and associated revenue will eventually disappear
with the glacier.
[3] Fortunately, Juneau has other attractions, including whale watching and rain
forests, and can maintain their status as a tourist destination, provided they can develop and enact
a plan for sustainable tourism.
Recent reports[4] have highlighted the hidden costs of tourism and the growing need to account
for and manage these costs to protect natural and cultural resources and build a sustainable
tourism industry on which numerous communities around the world depend. These hidden costs
include pressure on local infrastructure including drinking water supplies, waste management,
and an overall increased carbon footprint in tourist destinations, many of which lie in
environmentally sensitive regions. Local populations are also under pressure due to housing
supplies and costs, overcrowding, and rowdy tourists. Various measures have been enacted to
attempt to ease the burden, including increased hotel taxes, visitor fees, caps on the number of
daily visitors, and restrictions on alcohol sales and consumption. Additional revenue from taxes
have been used to support conservation, make improvements in infrastructure, and develop
community programs. While many locals that depend on tourism are concerned that additional
fees might drive tourists away and would rather see the numbers, and their businesses, grow,
many other locals are becoming disgruntled and either leaving or protesting against tourists.
• Build a model for a sustainable tourism industry in Juneau, Alaska. You may want to
consider factors such as the number of visitors, overall revenue, and measures enacted to
stabilize tourism. State clearly which factors you are optimizing, and which factors serve
as constraints. Include a plan for expenditures from any additional revenue and show how
these expenditures feed back into your model to promote sustainable tourism. Include a
sensitivity analysis and discuss which factors are most important.

Demonstrate how your model could be adapted to another tourist destination impacted by
overtourism. How does the choice of location effect which measures will be most
important? How might you use your model to promote attractions and/or locations that
have fewer tourists to develop a better balance?
• Write a one-page memo to the tourist council of Juneau outlining your predictions, the
effects of various measures, and your advice on how to optimize outcomes.

现在你的团队致力于解决以上提到的问题，请你给出几个关键词供相关文献的搜索

Introduction
Over the last year, both scholars and policymakers have recognized
the negative implications of tourism activities on both surrounding
environment (e.g. pollution, ecosystem degradation and overexploitation) and socio-economic background (e.g. damaging or loss of
local traditional cultures and networks) (Zhong et al., 2011). However,
on the reverse side, if proper planning and management practices are
implemented, tourism-related activities have a clear potential for either
boosting local economies and protecting their social and natural capital
(Sun et al., 2020). The economic relevance of tourism is clear in the
European context, where almost 10% of GDP and around 20 million jobs
can be attributed to this sector. Accordingly, European Commission has
recognized that tourism has largely contributed to boost growth,
generate new job opportunities and attract investments (European
Commission, 2006). Furthermore, tourism largely depends on the
attractiveness of tourist localities (Romao, 2020). Therefore, it is in the
interest of both tourism services providers and policymakers preserving
natural environment, social and cultural peculiarities and local wellbeing (Hollinshead, 1991). At tourist destinations, increasing the quality
of life of residents by maximizing the economic benefits, protecting
nature and providing visitors with high quality experiences is a main
goal for sustainable tourism activities. The Agenda for sustainable and
competitive European tourism recognizes the existence of a dual interaction between tourism and the protection of the distinctive social and
environmental local features: (i) the relevance of these issues is widely
recognized and their protection is directly supported; (ii) it becomes
economically advantageous for local agents to protect environmental
and socio-cultural heritage (European Commission, 2007). With these
premises, over the last decades, the idea of tourism as a powerful
channel to promote sustainability has rapidly spread across scholars and
policymakers (Yadav et al., 2018). Thus, the definition of sustainable
tourism deals with reconciling positive and long-term economic effects
with social equity and natural capital preservation (Swarbrooke, 1999).

• Corresponding author.
  E-mail addresses: [email protected] (R. Boffardi), [email protected] (L. De Simone), [email protected] (G. Ioppolo).
  Contents lists available at ScienceDirect
  Journal of Environmental Management
  journal homepage: http://www.elsevier.com/locate/jenvman
  https://doi.org/10.1016/j.jenvman.2021.112016
  Received 21 July 2020; Received in revised form 26 November 2020; Accepted 17 January 2021
  Journal of Environmental Management 285 (2021) 112016
  2
  These features pose sustainable tourism practices as a promising tool to
  achieve the sustainable development goals (SDGs) stated by the UN
  2030 Agenda1 “to end poverty, protect the planet and ensure prosperity
  for all” (Siakwah et al., 2020). Indeed, in spite of the absence of a clear
  reference to tourism in the Agenda, six Goals implicitly recognize the
  relevance of this economic sector for sustainable development (UNDP,
  2015; UNWTO, 2011). Implicit references can be identified in SDGs 8,
  12 and 14, which regard: (i) inclusive and sustainable economic growth,
  (ii) sustainable consumption and production (SCP) and (iii) sustainable
  use of oceans and marine resources, respectively. At the same time, the
  achievement of sustainable tourism targets must account for and,
  simultaneously, balance the interests of different stakeholders – i.e.,
  local population, entrepreneurs, etc. – in all the phases of policymaking
  (Garcia-Melon et al., 2012). Similarly, Goal 16 deals with justice and
  institutions as tools for promoting inclusive equitable development,
  regarding tourism governance (Emas, 2015). In the context of a wide
  policy and literature support to sustainable tourism, several initiatives
  have been implemented all over the world. Among these projects,
  Kasbah du Toubkal is a small lodge in the midst of a Berber community in
  Morocco, whose mission is to promote tourism while both avoiding
  negative effects of mass tourism developments and promoting employee
  education by re-investing profits. Similarly, Juist Island project (Germany), Greenest hotels in Thailand (Tongsai Bay), Gili Lankanfushi and
  the Coral Line Project (Maldives) have been recognized as best practices
  in the sector. However, in spite of this background, a framework for
  supporting investment decisions in sustainable tourism initiatives is
  missing.
  Furthermore, over the last months, the Covid-19 pandemic has
  dramatically reduced tourist numbers, posing the problem of identifying
  new solutions for correctly planning tourist initiatives and channelling
  flows without enhancing the spread of the virus (Reza Farzanegan et al.,
  2020). In addition, if the recovery of tourist areas after the pandemic
  will be guided by authorities and tourist organization according to
  appropriate measures (i.e., accounting for social, environmental and
  economic issues) the social costs of tourism will reduce (Qiu et al.,
  2020). In fact, despite the steadily increasing tourism inflows experienced over the last decades by several areas, many of them still lack a
  clear international destination image allowing them to exploit the
  benefit of international tourism (Della Corte et al., 2015). Therefore,
  several promotion activities might be carried out by, in order to increase
  the attractiveness of urban areas, by supporting the exploitation of the
  natural, historical, artistic and cultural heritage.
  As also recognized by the literature, tourism sustainability is only
  achievable if local population interests are protected, natural resources
  preservation is posed among its goals by authorities, citizens and service
  providers and, finally, local social capital is constantly enhanced by the
  implemented tourism policies (Garcia-Melon et al., 2012). Furthermore,
  in order to achieve environmental security, both local population and
  tourists have to be made aware of environmental risks inherent in
  tourism activities (Petrosillo et al., 2009). However, decision-making is
  a crucial moment of the planning cycle, since multiple actors – e.g. interest groups, institutions, private actors – strategically interact with
  each other. By contrast, from the point of view of private actors, sustainable lifecycle assessment becomes fundamental for determining the
  efficiency in each process by simultaneously controlling environmental
  impact (Vila et al., 2015). Indeed, several issues might hamper the
  achievement of these goals. First, when formulating tourism policies,
  several actors have to be taken into account – i.e., policymakers, tourists,
  host communities (Adongo et al., 2018). These stakeholders present
  different and, often conflicting interests (Onder ¨ et al., 2013; Petrosillo
  et al., 2010). Thus, consultation and collaboration among the stakeholders is fundamental to balance all the involved interests (Ballantyne
  et al., 2009; Petrosillo et al., 2009). In addition, Public Administration is
  increasingly required to solve decision problems characterized by the
  necessity of expenditure rationalization. This issue forces decisionmakers to define priorities of actions according to sets of variables other
  than merely economic ones – such as social, environmental, and cultural
  variables (Fraiz et al., 2020).
  Thus, the promotion of sustainable development within the framework of tourism policies can only be addressed by implementing environmental governance mechanisms accounting for all these issues and
  related risks (Petrosillo et al., 2009; Lozano-Oyola et al., 2019). Such a
  managerial approach to sustainability and ecology is integral to the
  documents presented by the UNWTO on the achievement of SDGs and,
  overall, to the policy recommendations aiming at promoting SDGs (Hall,
  2019). The strategic approach required to planning should be a
  goal-oriented, participatory and comprehensive one (Tan et al., 2018).
  Effective and efficient management of complex issues requires sophisticated instruments and tools to be integrated in the internal
  decision-making processes. Literature has proposed a wide set of instruments, each relying on different methodologies, which might be
  ascribed to two broad groups: Multi-dimension Criteria Analysis
  (MCDA) and multi-objective optimization techniques (Soltani et al.,
  2015). The former group comprehends a wide set of multidisciplinary
  approaches, allowing to either formulate rankings among alternatives or
  eliminating inefficient ones, according to economic, social, environmental, aesthetic and ethical concerns (Rostirolla, 1998). The latter
  exploits different calculation procedure and algorithms to identify the
  optimal and best-compromise solutions among a set of available alternatives (Arbolino et al., 2018).
  In this framework, the following research is aimed at proposing a
  methodology to assess and select tourism-related projects, in order to
  increase the efficiency in resource allocation and minimize socioenvironmental impacts on the territories. A comparison between the
  optimization model (i.e. the proposed approach) and the traditional
  multicriteria methods (i.e. weighted sum and AHP) allows to assess the
  goodness of our methodology. To test our, we hypothesise a generic call
  for tender drafted by a Public administration willing to promote sustainable tourism through the financing of a set of projects. Projects to be
  funded are selected based on a multi-objective optimization model accounting for social, environmental, and economic sustainability principle. In order to test the goodness of the proposed approach, we compare
  the result with other multicriteria techniques: namely, “weighted sum”
  and “Analytic Hierarchical Process”. Our research participates in the
  ongoing debate on the methodologies used to support decision-makers
  in promoting sustainable tourism (Garcia-Melon et al., 2012; Aljerf,
  2015). The proposed approach supports policymakers in the selection of
  initiatives to be funded in the tourist sector, providing suggestions to
  optimize the allocation of public resources. Basing on both the reference
  legislation – i.e. the call for tender - and a set of environmental, economic and social constraints, it will enable decision-makers to implement effective, comprehensive and goal-oriented ex-ante evaluation of
  the interventions.
  The paper is structured as follows. The second section shows the
  main techniques exploited as a decision support system. The third section presents the complexity of the tourism decision process and the
  different methodologies to solve it. Section four and five show and discusse the results. Conclusions are presented in Section six.

请你概括这段文字讲了什么

什么是MCDA

2. Methodological approaches applied to tourism-policy making
   Over the whole process of tourism policymaking process, a variety of
   relationships and interests surrounding the tourism sector must be
   considered. This array generates multi-decision maker, multi-objective,
   multi-criteria and multidimensional decision problems. Therefore, in
   the framework of tourism policies, the application of traditional evaluation techniques resorting to monetary values – such as cost-benefit
   analysis – is difficult and, often, unsuccessful (Douissa and Jabeur,
   2020). Based on these concerns, several techniques have been exploited
   to facilitate decision making in tourism policy planning and implementation, such as the construction of synthetic indicators (Blancas
   et al., 2010), theoretical modelling (e.g., Evolutionary game theory;
   Blanco et al., 2009), Multidimensional Analysis (Carrillo and Jorge,
   2017).
   Among the vast array of techniques, Multi-Criteria dimension analysis (MCDA) methods allow to simultaneously address many issues
   related to tourism policymaking (Cinelli et al., 2014). These techniques
   are multidisciplinary approaches to complex decision problems, aiming
   at simultaneously accounting for economic, social, environmental,
   aesthetic and ethical concerns by evaluating the impacts of either projects, plans or policies based on their original measurement scales
   (Rostirolla, 1998). Furthermore, MCDA techniques leave the final choice
   on the alternative(s) to be selected to the decision-makers, choosing on
   the basis of stated objectives, interests, and values, or, alternatively, past
   experience (Soltani et al., 2015; Baba and HakemZadeh, 2012). Indeed,
   given the plurality of decision-makers and stakeholder involved, no
   unique optimal solution can be identified. Therefore, MCDA techniques
   aim at identifying a combination of alternatives to be modified, in order
   to achieve the best compromise solution (an equilibrium which cannot
   be modified without reducing the utility of at least one of the stakeholders involved).
   Once defined the decision problem, when applying techniques
   belonging to the first groups, the first step consists in eliminating
   “inefficient” alternatives (Arbolino et al., 2018). In doing so one could
   refer to the concept of “dominance” (or “Pareto-efficiency”), according
   to whom an alternative is dominated if there is, at least, one different
   and preferable option in terms of, at least, one attribute (leaving the
   other constant) (Tan et al., 2010; Guo and Yang, 2009). Otherwise,
   alternative might be eliminated because, despite not being “dominated”
   ones, they do not satisfy some exogenously determined comparison
   criteria. This selection might be performed by resorting to either
   conjunctive (an alternative is selected if it achieves “excellent” scores in
   at least one attribute) or disjunctive (an alternative is deleted if it does
   not achieve “sufficient” scores in all the parameter) methods. The second
   group of techniques might be further ranked, by distinguishing between
   techniques using equal weighting and techniques applying weights
   calculated according to their operational sheets. Within the first group,
   two ordering techniques can be identified: maximin, establishing the
   overall performance of each alternative as the lowest value achieved by
   one of its attributes, and maximax, calculating the overall performance
   of each alternative based as the highest value achieved by one of its
   attributes.
   The most frequently applied techniques may be traced back to the
   second group of ordering techniques (i.e., those applying different
   weighting), including:
   • Weighted sum, classifying alternatives based on the weighted sum of
   the values achieved by each attribute of the alternative (Fishburn,
   1967);
   • Weighted Product, ranking alternatives based on the weighted product of the values achieved by each attribute of the alternative.
   Differently from the previous one, this technique strongly penalises
   alternatives achieving low scores in one or more alternatives (Miller
   and Starr, 1969);
   • Minimum distance from the target, ranking alternatives according to
   their distance from a set of targets established ex-ante;
   • Minimum desirable value, obtaining a ranking through the weighted
   sum of the distance of each alternative from some threshold, representing the minimum values achievable, according to the decisionmaker preferences (Rostirolla, 1998).
   • Technique for Order Preference by Similarity to Ideal Solution (TOPSIS),
   ranking alternatives by simultaneously accounting for the distances
   from both “ideal” and “worst” solutions. This technique was elaborated by Hwang and Yoon (1981).
   • Electre Methods aim at (i) preselecting (Electre I) or (ii) ranking alternatives (Electre II, III, IV) (Roy, 1991). Differently from the previously mentioned techniques (mainly from the weighted sum), this
   group of techniques do not rely on a “compensatory” approach but,
   rather, on a deterministic one. This technique requires the identification of several thresholds (i.e., concordance and discordance indexes), meant as the limits within which the decision-maker is
   available to express a judgement in case a conflict arise among two or
   more alternatives. All the alternatives exceeding these thresholds are
   listed in a final ranking (Electre II, III, IV).
   • Analytic Hierarchy Processes (AHP; Saaty, 1988), allowing to deal
   with decision problems assessed by qualitative data, based on pairwise comparisons. It proceeds as follows: first, the problem has to be
   broken down into elementary sub-problems (hierarchical decomposition); subsequently, pairwise comparisons are performed among all
   the elements grouped in the same hierarchical level; finally, the
   decision problem is reassembled and alternatives are ordered. An
   extension of this model has been elaborated and called Analytic
   Network Processes (ANP).
   • Preference Ranking Organization Method for Enrichment Evaluation
   (PROMETHEE) and its descriptive complement Geometrical Analysis
   for Interactive Aid (GAIA) (Brans et al., 1986). It is a set of outranking
   techniques aimed at achieving partial (PROMETHEE I) or complete
   rankings (PROMETHEE II, which is the basis for the following versions: PROMETHEE III to VI). It is based on five subsequent steps: (i)
   calculation of the deviations based on pair-wise comparisons; (ii)
   application of relevant preference function to each criterion; (iii)
   determination of the global preference index; (iv) calculation of
   either positive and negative outranking flows; (v) ranking construction based on net outranking flows calculation (Behzadian et al.,
   2010).
   • The Dominance-based Rough Set Approach (DRSA) is a relatively new
   automated valuation methodology for mass appraisal. Differently
   from the Classical Rough Set Approach (CRSA), DRSA modifies the
   indiscernibility principle by applying a dominance principle. In this
   model, data are not organized in value classes, with the aim of
   estimating a value interval for each alternative in terms of “at least”
   and “at most” values (Cinelli et al., 2014).
   These techniques are intended to achieve the best-compromise solutions among the most relevant objectives, thus waiving the paradigm
   of “optimality”. Tourism policymakers express a huge set of heterogeneous goals to be achieved through the allocation of public resource
   (Stevenson, 2007). This provides room for the application of MCDA
   methods. Table 1 lists studies applying MCDA technique to sustainable
   tourism problems.
   It is worth mentioning the third group of methodologies, namely the
   optimization methodologies. By resorting to different calculation procedure and algorithms, these techniques allow to identify the optimal
   and best-compromise solutions among a set of available alternatives
   (Arbolino et al., 2018). According to the literature, these techniques can
   be an effective and feasible instrument to improve tourism planning and
   contemporarily achieve sustainable goals (Yu, 2015).
   Decision Support Systems based on multi-objective techniques allow
   for a feasible, effective and useful appraisal of the effects of tourism
   policies and a subsequent improvement of their sustainability (Shcherbina and Shembeleva, 2014). As a consequence, the objective of this
   research has been to show the operative advantages deriving from the
   exploitation of “constrained” multi-objective optimization techniques,
   within the planning phase of sustainable tourism initiatives. This goal is
   achieved through the identification of the “best-compromise” public
   resource allocation to the tourism sector.

请你概括这段文字讲了什么，对我们研究的问题有什么帮助

Juneau, Alaska, USA with a population of about 30,000 residents, set a record in 2023 with 1.6
million cruise passengers, hosting as many as seven large cruise ships on the busiest days, with
upwards of around 20,000 visitors.
[1] While these tourists bring in substantial revenue for the
city, on the order of $375 million,
[2] they also bring issues related to overcrowding that have the
city working to limit the number of guests. Ironically, Mendenhall Glacier, one of the premier
attractions in Juneau, has been receding, primarily due to warming temperatures caused, in part,
by overtourism. The glacier has receded the equivalent of eight football fields since 2007,
leading many locals to worry that the tourists and associated revenue will eventually disappear
with the glacier.
[3] Fortunately, Juneau has other attractions, including whale watching and rain
forests, and can maintain their status as a tourist destination, provided they can develop and enact
a plan for sustainable tourism.
Recent reports[4] have highlighted the hidden costs of tourism and the growing need to account
for and manage these costs to protect natural and cultural resources and build a sustainable
tourism industry on which numerous communities around the world depend. These hidden costs
include pressure on local infrastructure including drinking water supplies, waste management,
and an overall increased carbon footprint in tourist destinations, many of which lie in
environmentally sensitive regions. Local populations are also under pressure due to housing
supplies and costs, overcrowding, and rowdy tourists. Various measures have been enacted to
attempt to ease the burden, including increased hotel taxes, visitor fees, caps on the number of
daily visitors, and restrictions on alcohol sales and consumption. Additional revenue from taxes
have been used to support conservation, make improvements in infrastructure, and develop
community programs. While many locals that depend on tourism are concerned that additional
fees might drive tourists away and would rather see the numbers, and their businesses, grow,
many other locals are becoming disgruntled and either leaving or protesting against tourists.
• Build a model for a sustainable tourism industry in Juneau, Alaska. You may want to
consider factors such as the number of visitors, overall revenue, and measures enacted to
stabilize tourism. State clearly which factors you are optimizing, and which factors serve
as constraints. Include a plan for expenditures from any additional revenue and show how
these expenditures feed back into your model to promote sustainable tourism. Include a
sensitivity analysis and discuss which factors are most important.

Demonstrate how your model could be adapted to another tourist destination impacted by
overtourism. How does the choice of location effect which measures will be most
important? How might you use your model to promote attractions and/or locations that
have fewer tourists to develop a better balance?
• Write a one-page memo to the tourist council of Juneau outlining your predictions, the
effects of various measures, and your advice on how to optimize outcomes.

你是一名资深分析师与可持续旅游规划师，请你分析这篇文献对以上问题的解决有何帮助，并给出具体公式与方法