Dugaan bahwa kategori nomor (5) di alinea berikut #PeringkatIndonesia buruk karena hutangnya banyak perlu dikesampingkan. Dugaan bahwa harapan hidup di Indonesia dengan damai dan sehat hingga tua (2) juga perlu dikesampingkan. Dugaan bahwa polusi karbon (6) di Indonesia masih tertolong hutan tropis dsb, juga sangat perlu dikesampingkan. Inilah tulisan fakta riset World Economic Forum tentang Indonesia. Ingat Indonesia lumayan juara mispersepsi Per definisi pakai bahasa (diupayakan) sederhana, Indeks Pembangunan Inklusif (IBI) bicara apakah kebijakan struktur dan kelembagaan sebuah perekonomian sudah pro pada: (1) Penciptaan lapangan pekerjaan, (2) Harapan hidup sehat, (3) Sedikit orang miskinnya, (4) Merata kemakmurannya, (5) Sedikit proporsi hutang negaranya, dan (6) Polusi karbonnya dari ekonominya minimal. Ini baru sebagian dari sub pilar dan pilar lainnya, untuk teknisnya dapat menjadi bahan diskusi lebih jauh. Memakai kategori peringkat 'Di Kelas' a la aba-amba maka ...
Bridging demand and supply proves to be a success formula to get supernormal profit in the case of applications-based public transport . Initially the demand (in the form of ease of meeting the main needs of commuting) is far enough away from the supply (which is still a simple and complicated method of meeting the demand). Puskakom Universitas Indonesia in its latest findings on application-based public transportation in Jakarta, Indonesia revealed 2/3 more respondents are users of this type of transportation and 2/3 more than users are women. The reason for the + -2.800s of the users of this user is the sense of security and convenience.
A doctoral dessertation at the University of North Texas, USA by Rebecca A. Scott describes a causal loop diagram in describing the determinants of decision making factors affecting attitudes toward public transport. On the right side of the diagram are described the interdependent relationships of demand and supply of public transport with attitudes toward public transport. Improved attitudes will increase demand and make local population's commuters trigger more supply from public transport providers in order to meet that particular demand. On the left side are described four main factors which are convenience, security, price and then knowledge; all those explain +- 1/4 of all attitudes towards the public transport system.
Electronic Word of Mouth (eWOM)
Rebecca also collected data from 495 respondents of public transport user in large metropolitan areas in the southwestern region in the United States and analyzed customer online comments and incorporated them into four explanatory attitudes of public transportation trends that also validate the above model. Also illustrated here the distance between each factor in decision making. A slight difference is in convenience clusters that are broken down into personal convenience and time-related convenience; as well as the emergence of a new cluster: parking. The cluster number 7 that is in the personal convenience lopp for example, contains the keyword: + little + station + clean + minutes + home + driving discussed 85 times (9%); While cluster number 5 about parking with keyword: + gasoline + money saving + parking + work + driving discussed as much as 37 times (4%).
The source of word-of-mouth information in the post-truth era now clearly influences many parties' decision-making process including those users of public transportation.
Application-based public transportation service providers in partnership with local Government clearly obtain (supernormal profit in the case of providers) and provide public benefits (to public) in solving transportation issues in major cities. It now remains a challenge to continue this influencial diagram resulting in a not only sporadically served public transportation demand by providers and local government but far ahead also increases the interaction of urban communities in achieving a higher quality of life.
A doctoral dessertation at the University of North Texas, USA by Rebecca A. Scott describes a causal loop diagram in describing the determinants of decision making factors affecting attitudes toward public transport. On the right side of the diagram are described the interdependent relationships of demand and supply of public transport with attitudes toward public transport. Improved attitudes will increase demand and make local population's commuters trigger more supply from public transport providers in order to meet that particular demand. On the left side are described four main factors which are convenience, security, price and then knowledge; all those explain +- 1/4 of all attitudes towards the public transport system.
Electronic Word of Mouth (eWOM)
Rebecca also collected data from 495 respondents of public transport user in large metropolitan areas in the southwestern region in the United States and analyzed customer online comments and incorporated them into four explanatory attitudes of public transportation trends that also validate the above model. Also illustrated here the distance between each factor in decision making. A slight difference is in convenience clusters that are broken down into personal convenience and time-related convenience; as well as the emergence of a new cluster: parking. The cluster number 7 that is in the personal convenience lopp for example, contains the keyword: + little + station + clean + minutes + home + driving discussed 85 times (9%); While cluster number 5 about parking with keyword: + gasoline + money saving + parking + work + driving discussed as much as 37 times (4%).
The source of word-of-mouth information in the post-truth era now clearly influences many parties' decision-making process including those users of public transportation.
Application-based public transportation service providers in partnership with local Government clearly obtain (supernormal profit in the case of providers) and provide public benefits (to public) in solving transportation issues in major cities. It now remains a challenge to continue this influencial diagram resulting in a not only sporadically served public transportation demand by providers and local government but far ahead also increases the interaction of urban communities in achieving a higher quality of life.
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