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"The tourism and travel sector has contributed significantly to Indonesia’s economic growth and robust development. Despite its positive impact, tourism and travel business activities also potentially impact environmental loss. In order to reduce these negative impacts, the new concept of tourism, namely low-carbon tourism, which focuses on environmental sustainability, can be implemented as the enabler. One of the factors that can support the implementation is the existence of environmentally friendly technology that requires a technology transfer process. This paper aims to overview the role and implication of technology transfer for enabling low-carbon tourism in Indonesia and outlining a conceptual framework for addressing the political (P), economic (E), social (S), technological (T), environmental (E), and legal (L) factors that constrain and support in enabling low-carbon tourism through technology transfer in Indonesia. A qualitative library research method and PESTEL analysis were employed to analyze and map the implications of external factors influencing the development of low-carbon tourism through technology transfer in Indonesia. The paper denotes that all the factors (political, economic, social, technological, environmental, and legal) were interrelated. Nevertheless, the economic factor was the only one with a moderate policy to encourage businesses to use green practices, particularly for the carbon tax policy. Consequently, there was still an opportunity for monetary policy to promote low-carbon tourism."

"ABSTRAKPenelitian ini bertujuan untuk menganalisis nilai ekonomi Taman Wisata Alam (TWA) Angke Kapuk di kota Jakarta Utara dengan menggunakan metode biaya perjalanan dan untuk memperkirakan permintaan pengunjung dan kemauan untuk membayar (willingness to pay/WTP). Data untuk penelitian ini dikumpulkan dengan melakukan survei pada 100 sampel pengunjung. Data dianalisis dengan menggunakan model regresi log-log. Hasil penelitian ini menunjukkan bahwa biaya perjalanan dan pendapatan mempengaruhi total kunjungan individu dan menunjukkan bahwa rata-rata kesediaan pengunjung untuk membayar adalah Rp.276.921 per individu per tahun. Nilai ekonomi dari TWA Angke Kapuk yang berasal dari kesediaan untuk membayar pada Tahun 2014 diproyeksikan sebesar Rp.2,42 miliar. Saat ini, kebijakan untuk menaikan tarif masuk adalah solusi yang mungkin untuk membiayai konservasi.

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ABSTRACTThis research aim to evaluate the economic value of Angke Kapuk natural tourism park (TWA Angke Kapuk) in North Jakarta by travel cost method and to estimate the demand for traveling and the willingness to pay. The data for this research were collected by conducting surveys on 100 sample visitors. The data were analyzed by using log-log regression model. The result of this research indicated that travel cost and income affected total individual visits and showed that visitors’ average willingness to pay was Rp.276.921 per head per year. The economic value of TWA Angke Kapuk in 2014 is projected to reach Rp.2.42 billion. At present, the policy to increase entrance fees is a possible solution to finance conservation."

"ABSTRAK

Model perencanaan perjalanan telah berkembang dari faktor kuantitatif yaitu pencapaian waktu tersingkat menjadi faktor kualitatif yaitu pencapaian kepuasan. Kepuasan ini didapatkan dari kunjungan ke sejumlah tempat yang dianggap penting, kritis, atau favorit sesuai lingkup model tersebut. Penerapan dalam bidang pariwisata akan membantu wisatawan dalam pembentukan rute perjalanan pariwisata yang layak dan berkualitas tinggi. Model yang dikembangkan pada penelitian ini adalah Team Orienteering Problem with Time Windows (TOPTW). Pada model awal dilakukan penyusunan rute dengan memperhatikan prioritas wisatawan, maksimum total waktu yang dimiliki wisatawan, lokasi awal yang sama dengan lokasi akhir, serta jam operasional destinasi wisata (time window). Penelitian perencanaan perjalanan wisata ini mengubah model awal dengan melakukan penyesuaian kebutuhan wisatawan yang belum terpenuhi dan mencapai tujuan kedua yaitu minimum total waktu yang dibutuhkan. Model usulan memperhatikan waktu kedatangan yang diinginkan wisatawan, lokasi awal dan akhir yang berbeda, serta toleransi waktu yang ditetapkan wisatawan terhadap jam buka dan jam tutup suatu destinasi, serta hari operasional destinasi wisata. Wisatawan juga dapat mengubah waktu kunjungan (service time), skor destinasi yang menunjukan tingkat kefavoritan, dan menentukan waktu kedatangan ke destinasi wisata.

            Metode yang digunakan bertujuan untuk mencari keseimbangan (equilibrium solution) antara hasil yang optimal dengan proses perhitungan yang lebih efisien. Metode pencarian hasil akan diawali dengan kontruksi heuristik untuk mengakomodasi destinasi favorit terlebih dahulu dalam rute, dilanjutkan dengan tahapan local search untuk mendapatkan pengaturan terbaik dari rute-rute tersebut. Metode yang digunakan adalah Iterated Local Search (ILS) yang disesuaikan, yaitu Adjusted ILS (AILS). AILS terdiri dari tahapan permutasi dan reversed untuk setiap rute, dan terakhir adalah perturbasi untuk semua rute yang terbentuk. Pada setiap tahapan akan dibandingkan total skor dan total waktunya, dan yang terbaik akan melanjutkan ke tahapan berikutnya. Setiap tahapan ini akan melalui diverifikasi untuk menjamin kelayakan hasil.

            Selain itu dilakukan perbandingan metode antara AILS dan metode metaheuristik lain seperti Multi-start Simulated Annealing (MSA), Simulated Annealing (SA), Artificial Bee Colony (ABC) dan ILS. Hasil dari uji statistik menyatakan adanya perbedaan hasil di antara metode AILS dan metode-metode lainnya. Metode AILS memiliki keunggulan lebih tingginya skor per destinasi yang berarti lebih banyak destinasi favorit yang dikunjungi yaitu rata-rata sebesar 26% untuk metode MSA, SA, dan ABC, dan 21% untuk metode ILS. Running time pada AILS lebih singkat 537% daripada metode MSA, SA dan ABC, dan lebih lama 42% dibandingkan metode ILS. Semua metode yang dibandingkan tidak memiliki total waktu seperti yang telah dilakukan dalam AILS. Setelah itu dibuat sistem rekomendasi bernama ROSTER (Routing System Recommendation)  untuk kemudahan penggunaan dan pemahaman hasil.

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ABSTRACT

 

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The travel planning model has expanded from quantitative factor with the achievement of the shortest time, into a qualitative factor with the achievement of satisfaction. The satisfaction is obtained from visiting a number of destinations that are considered important, critical, or favorite. Application in the tourism industry will help tourists to develop an appropriate and high-quality travel routes. The development model in this study is Team Orienteering Problem with Time Windows (TOPTW). In the initial model, route planning considers tourist priorities, the maximum total time owned by tourists, the same initial location as the final location, and the operational hours of each destination or time window. This research develop the initial model by adjusting more demand of tourists and achieve the second goal, the minimum total time. The proposed model consider arrival time of tourists, different initial and final locations, time tolerance from tourists to destination operational hours, and operational days of the destinations. Tourists can also adjust the time of visit or service time, destination scores that indicate the level of favorability, and determine the time of arrival to tourist destinations.

The method used aims to find a balancing (equilibrium solution) between optimal results with  more efficient running time. The method will begin with a heuristic construction to accommodate the favorite destinations in advance on the route, followed by the local search to get the best routes. The method used is modification of Iterated Local Search (ILS) and being Adjusted ILS (AILS). AILS consists of permutation and reversed stages for each route, and perturbation for all routes formed in previous stages. At each stage the total score and total time will be compared, and the best routes will proceed to the next stage. Each of these stages will be verified through to ensure the feasibility of the results.

A comparison method was conducted between AILS and other metaheuristic methods such as Multi-start Simulated Annealing (MSA), Simulated Annealing (SA), Artificial Bee Colony (ABC) and ILS. The results of the statistical test revealed differences in results between the AILS method and other methods. The AILS method has the advantage of higher scores per destination which means more favorite destinations visited are on average 26% for the MSA, SA, and ABC methods, and 21% for the ILS method. Running time on AILS is 537% shorter than MSA, SA and ABC methods, and 42% shorter than ILS method. All the previous methods do not have the minimum total time that was reached in AILS. A recommendation system named ROSTER (Routing System Recommendation) was made for user convenience.

 

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"Sustainability remains one of the major issues in tourism today. Concerns over climate and environmental change, the fallout from the global economic and financial crisis, and the seeming failure to meeting UN Millennium development goals have only reinforced the need for more sustainable approaches to tourism, however they be defined. Given the centrality of sustainability in tourism curricula, policies, research and practice it is therefore appropriate to prepare a state of the art handbook on the relationship between tourism and sustainability. This timely Handbook of Tourism and Sustainability is developed from specifically commissioned original contributions from recognised authors in the field, providing a systematic guide to the current state of knowledge on this area. It is interdisciplinary in coverage and international in scope through its authorship and content. The volume commences with an assessment of tourism's global environmental, e.g. climate, emissions, energy use, biodiversity, water use, land use, and socio-economic effects, e.g. economic impacts, employment and livelihoods, culture. This then provides the context for the following sections that describe the main theoretical frameworks and constructs that inform tourism and sustainability, management tools and approaches, and the approaches used in different tourism and travel industry sectors. The book concludes by examining emerging and future concerns in tourism and sustainability such as peak-oil, post-carbon tourism, green economy and transition tourism"