This paper explores and validates the process of customer value creation in self-service technologies(SSTs)in the context of the tourism industry.As the self-technology has been gradually advanced,its adoption in the ...This paper explores and validates the process of customer value creation in self-service technologies(SSTs)in the context of the tourism industry.As the self-technology has been gradually advanced,its adoption in the tourism industry has brought many changes.A new trend of self-service technologies has helped service firms to save the labor costs and customers’waiting time for transactions.The purpose of this study is to confirm an applicability and a design of the original model of SSTs and explore the connection between SSTs and creation of value perception through a confirmatory factor analysis in the context of the tourism industry.Furthermore,the results of the online survey questionnaire from 234 responses in the United States and South Korea are explained in this study.The results of this study concluded that five statistically important factors are related to customers’motivations to use SSTs and enable customers to interact with SSTs as“SST location and capacity planning”,“SST service quality”,“motivations to use SST”,“SST design”,and“SST encounter”.These factors may imply an important meaning to better understand about customer value during the adoption of SSTs in the tourism industry.Tourism firms may use the results of this study to effectively enhance how customers perceive value about their products and services during the usage of SSTs.This will help tourism firms’efficiencies on the adoption of SSTs for their business plans and help them remain profitable in the competitive market.展开更多
The study investigated the impacts of tropical cyclone (TC) Fantala (11<sup>th</sup> to 27<sup>th</sup> April, 2016) to the coastal areas of Tanzania, Zanzibar in particular. Daily reanalysis d...The study investigated the impacts of tropical cyclone (TC) Fantala (11<sup>th</sup> to 27<sup>th</sup> April, 2016) to the coastal areas of Tanzania, Zanzibar in particular. Daily reanalysis data consisting of wind speed, sea level pressure (SLP), sea surface temperatures (SSTs) anomaly, and relative humidity from the National Centres for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) were used to analyze the variation in strength of Fantala as it was approaching the Tanzania coastal line. In addition observed rainfall from Tanzania Meteorological Authority (TMA) at Zanzibar office, Global Forecasting System (GFS) rainfall estimates and satellite images were used to visualize the impacts of tropical cyclone Fantala to Zanzibar. The results revealed that, TC Fantala was associated with deepening/decreasing in SLP (from 1012 - 1010 mb) around the north-western Madagascar and coastal Tanzania, whereas the mean SSTs was greater than 28<span style="white-space:nowrap;">°</span>C and an SSTs anomaly ranged from 0 to 2.3<span style="white-space:nowrap;">°</span>C. The vertical wind shear which ridged at Mozambican Channel and over north-eastern Madagascar was high enough (12 - 15 ms<sup>-1</sup>) to support the intensifying of Fantala. The thermodynamic and dynamic conditions of Fantala influenced heavy rainfall of greater than 170 mm over most stations in Zanzibar. Moreover, Fantala disrupted the temporal variability of 2016 March to May (MAM) seasonal rainfall. Besides, more than 420 people were homeless, at least 3330 houses were destroyed, and about 2 people died. As for mainland Tanzania Fantala resulted in a death of 12 people in Kilimanjaro and Arusha, more than 315 houses were washed away by flooding leading to 13,933 people being homeless. Conclusively the study calls for an extensive research work based on examining and forecasting the TCs rainfall impacts and their contribution during the two rainfall seasons of OND and MAM in Tanzania.展开更多
This article examines the off season rainfall in northern coast Tanzania(NCT)including Zanzibar which occurred in January and February 2020(JF).Like the JF rainfalls of 2001,2004,2010,2016 and 2018,the JF(2020)rainfal...This article examines the off season rainfall in northern coast Tanzania(NCT)including Zanzibar which occurred in January and February 2020(JF).Like the JF rainfalls of 2001,2004,2010,2016 and 2018,the JF(2020)rainfall was more unique in damages including loss of lives,properties and infrastructures.The study used the NCEP/NCAR reanalysis data to examine the cause of uniqueness of JF rainfall in 2001,2004,2010,2016,2018 and 2020 over NCT and Zanzibar.These datasets include monthly mean u,v wind at 850,700,500,and 200 mb;SSTs,mean sea level pressure(MSLP)anomalies,Dipole Mode Index(DMI),and monthly rainfall from NCT and Zanzibar stations.Datasets were processed and calculated into long term,seasonal,and monthly averages,indeed,Precipitation Index(PI)was calculated.Correlation analysis between the rainfall(December to January),SST,DMI and 850 mb wind vectors;and long-term percentage contribution of investigated parameters was calculated.Results revealed significant positive and negative correlations between JF rainfall,SSTs and DMI.Moreover,JFs of 2004 and 2016 had higher rainfalls of 443 mm with percentage contribution of up to 406%,while January and February,2020 had the highest of 269.1 and 101.1mm in Zanzibar and 295 and 146.1 mm over and NCT areas,with highest January long-term rainfall contribution of 356%in Zanzibar and 526%over NCT.The DJF(2019/20)had the highest rainfall record of 649.5 mm in Zanzibar contributing up to 286%,while JF 2000 rainfall had a good spatial and temporal distribution over most NCT areas.JF,2020 rainfall had impacts of more than 20 people died in Lindi and several infrastructures including Kiyegeya Bridge in Morogoro were damaged.Conclusively,more research works on understanding the dynamics of wet and dry JF seasons should be conducted.展开更多
文摘This paper explores and validates the process of customer value creation in self-service technologies(SSTs)in the context of the tourism industry.As the self-technology has been gradually advanced,its adoption in the tourism industry has brought many changes.A new trend of self-service technologies has helped service firms to save the labor costs and customers’waiting time for transactions.The purpose of this study is to confirm an applicability and a design of the original model of SSTs and explore the connection between SSTs and creation of value perception through a confirmatory factor analysis in the context of the tourism industry.Furthermore,the results of the online survey questionnaire from 234 responses in the United States and South Korea are explained in this study.The results of this study concluded that five statistically important factors are related to customers’motivations to use SSTs and enable customers to interact with SSTs as“SST location and capacity planning”,“SST service quality”,“motivations to use SST”,“SST design”,and“SST encounter”.These factors may imply an important meaning to better understand about customer value during the adoption of SSTs in the tourism industry.Tourism firms may use the results of this study to effectively enhance how customers perceive value about their products and services during the usage of SSTs.This will help tourism firms’efficiencies on the adoption of SSTs for their business plans and help them remain profitable in the competitive market.
文摘The study investigated the impacts of tropical cyclone (TC) Fantala (11<sup>th</sup> to 27<sup>th</sup> April, 2016) to the coastal areas of Tanzania, Zanzibar in particular. Daily reanalysis data consisting of wind speed, sea level pressure (SLP), sea surface temperatures (SSTs) anomaly, and relative humidity from the National Centres for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) were used to analyze the variation in strength of Fantala as it was approaching the Tanzania coastal line. In addition observed rainfall from Tanzania Meteorological Authority (TMA) at Zanzibar office, Global Forecasting System (GFS) rainfall estimates and satellite images were used to visualize the impacts of tropical cyclone Fantala to Zanzibar. The results revealed that, TC Fantala was associated with deepening/decreasing in SLP (from 1012 - 1010 mb) around the north-western Madagascar and coastal Tanzania, whereas the mean SSTs was greater than 28<span style="white-space:nowrap;">°</span>C and an SSTs anomaly ranged from 0 to 2.3<span style="white-space:nowrap;">°</span>C. The vertical wind shear which ridged at Mozambican Channel and over north-eastern Madagascar was high enough (12 - 15 ms<sup>-1</sup>) to support the intensifying of Fantala. The thermodynamic and dynamic conditions of Fantala influenced heavy rainfall of greater than 170 mm over most stations in Zanzibar. Moreover, Fantala disrupted the temporal variability of 2016 March to May (MAM) seasonal rainfall. Besides, more than 420 people were homeless, at least 3330 houses were destroyed, and about 2 people died. As for mainland Tanzania Fantala resulted in a death of 12 people in Kilimanjaro and Arusha, more than 315 houses were washed away by flooding leading to 13,933 people being homeless. Conclusively the study calls for an extensive research work based on examining and forecasting the TCs rainfall impacts and their contribution during the two rainfall seasons of OND and MAM in Tanzania.
文摘This article examines the off season rainfall in northern coast Tanzania(NCT)including Zanzibar which occurred in January and February 2020(JF).Like the JF rainfalls of 2001,2004,2010,2016 and 2018,the JF(2020)rainfall was more unique in damages including loss of lives,properties and infrastructures.The study used the NCEP/NCAR reanalysis data to examine the cause of uniqueness of JF rainfall in 2001,2004,2010,2016,2018 and 2020 over NCT and Zanzibar.These datasets include monthly mean u,v wind at 850,700,500,and 200 mb;SSTs,mean sea level pressure(MSLP)anomalies,Dipole Mode Index(DMI),and monthly rainfall from NCT and Zanzibar stations.Datasets were processed and calculated into long term,seasonal,and monthly averages,indeed,Precipitation Index(PI)was calculated.Correlation analysis between the rainfall(December to January),SST,DMI and 850 mb wind vectors;and long-term percentage contribution of investigated parameters was calculated.Results revealed significant positive and negative correlations between JF rainfall,SSTs and DMI.Moreover,JFs of 2004 and 2016 had higher rainfalls of 443 mm with percentage contribution of up to 406%,while January and February,2020 had the highest of 269.1 and 101.1mm in Zanzibar and 295 and 146.1 mm over and NCT areas,with highest January long-term rainfall contribution of 356%in Zanzibar and 526%over NCT.The DJF(2019/20)had the highest rainfall record of 649.5 mm in Zanzibar contributing up to 286%,while JF 2000 rainfall had a good spatial and temporal distribution over most NCT areas.JF,2020 rainfall had impacts of more than 20 people died in Lindi and several infrastructures including Kiyegeya Bridge in Morogoro were damaged.Conclusively,more research works on understanding the dynamics of wet and dry JF seasons should be conducted.
