Geographical Determinants of Quantity and Rating of Online Hotel Reviews in Central Poland

2019 ◽  
Vol 53 ◽  
pp. 5-5 ◽  
Author(s):  
Tomasz Napierała ◽  
Katarzyna Leśniewska-Napierała
Keyword(s):  
Social Media ◽  
Control Variable ◽  
Media Management ◽  
Factors Affecting ◽  
Explanatory Variables ◽  
Average Value ◽  
Media Type ◽  
Central Poland ◽  
Geographical Factors ◽  
The Impact

Purpose. The aim of this enquiry is to determine the impact of various geographical factors on the rating and popularity of hotels in selected social media. Method. Research was conducted for all 193 star-ranked hotels operating in July 2017, in central Poland. However, analysis covered only those establishments which used all considered online review sources (118 star-ranked hotels). The criteria for the selection of social media were their popularity and the ability to rate the hotel by the guests. The analysed social media channels include: Booking.com, GoogleMaps, Facebook, TripAdvisor and Trivago. To achieve the research objective, 15 semi-logarithmic models were estimated to explain the variability of: 1) number of hotel reviews posted on social media sites, 2) average hotel ratings in social media, and 3) multiplied effect of quantity and average value of online hotel ratings; separately for each type of analysed social media. The following geographical explanatory variables were considered: 1) type of location (urban or rural), 2) distance from closest transport modes (road, rail and air), 3) distance to the nearest tourist attractions, 4) distance from the closest administrative centre, 5) distance from the nearest competing hotels. The hotel star-rank was a control variable included in the study. Findings. Among the analysed explanatory variables, the most important geographical factor conditioning the number of hotel service quality assessments in central Poland on social media sties was communication accessibility, and then, the closeness of competing hotels. Regardless of the type of social media, no significant influence of practically any of the analysed geographical determinants on the average value of ratings in social media was identified. Research and conclusions limitations: The models explained the observed variability of variables, finding hotel ratings in social media to be at an insignificant level, between 8% and 33%. Practical implications. Social media management is currently one of the key areas of marketing communication run by hotel enterprises. This article should make those who are responsible for managing social media in business practice more focused on geographical context. Originality. The article is the first known attempt to the authors to assess geographical factors affecting the rating and popularity of hotels in social media. Type of paper. The article presents findings from empirical research.

scholarly journals The Impact of GAP-SOP on The Production and Technical Efficiency of Garlic in Temanggung Regency

Agro Ekonomi ◽  
2019 ◽  
Vol 29 (2) ◽  
pp. 299
Author(s):  
Aristiyana Nur Tri Wardani ◽  
Dwidjono Hadi Darwanto
Keyword(s):  
Technical Efficiency ◽  
Sample Selection ◽  
Participation Rate ◽  
Simple Random Sampling ◽  
Technical Inefficiency ◽  
Factors Affecting ◽  
Average Value ◽  
Central Java ◽  
Efficient Level ◽  
The Impact

Temanggung regency is the largest garlic producer region in Central Java Province. However, its productivity is still low compared to the other regencies since garlic farmers have not achieved technical efficiency and limitary garlic farming technology.  Hence, it is necessary to investigate whether the input application in the process of garlic production has been at technically efficient level or not. This research aims to determine factors affecting garlic production, the level of technical efficiency and technical inefficiency of garlic farming in Temanggung Regency. The location of the research was determined by using purposive sampling. The sample selection used simple random sampling method with  60 garlic farmers as the respondent. The result shows that production factors such as land area, garlic seed, ZK fertilizer, pesticide and the level of application of garlic GAP-SOP have significant effect on garlic production. The average value of farmer’s technical efficiency is 0,811. It means that respondents in this study have been technically efficient. The socio-economic factors affecting technical inefficiency are the age, the number of worker in a family, the level of education and participation rate within farmer group. The improvement effort of technical efficiency of garlic farming can be done by optimizing the contribution of farmer group as a facility to access information. Therefore, it is able to improve the skills and knowledge of farmers to farm garlic.

scholarly journals The Determinants Of Population Health Spatial Disparities

2014 ◽  
Vol 17 (4) ◽  
pp. 173-185 ◽  
Author(s):  
Emilia Modranka ◽  
Jadwiga Suchecka
Keyword(s):  
Social Development ◽  
Access To Health Care ◽  
Health Care Services ◽  
Empirical Studies ◽  
Factors Affecting ◽  
Explanatory Variables ◽  
Spatial Disparities ◽  
Care Services ◽  
Number Of Factors ◽  
The Impact

Health of the population is one of the basic factors of social development. The results of empirical studies indicate a number of factors determining the level of health of the population related to access to health care services, the level of environmental pollution and the wealth of society. It must be assumed that the observed disparities in the health depend on distributions of particular determinants. The aim of the article is to assess the significance of the main factors affecting the occurrence of spatial disparities in the level of social development districts NTS-4 in terms of health of the population. The analysis was based on estimates of the Spatial Durbin Model (SDM) which takes into account the impact of neighborhood spatial units on level of dependent variable and the explanatory variables. The size of the level of social development in terms of health of the population in the study was approximate by the aggregate value of the index, which is the local component of the Local Human Development Index LHDI.

scholarly journals ANTESEDEN DAN KONSEKUEN PENGGUNAAN MEDIA SOSIAL BAGI UMKM: ANALISIS PERSPEKTIF ORGANISASI

2018 ◽  
Vol 19 (3) ◽  
pp. 12
Author(s):  
Anissa Hakim Purwantini ◽  
Friztina Anisa
Keyword(s):  
Social Media ◽  
Customer Service ◽  
Partial Least Square ◽  
Least Square ◽  
Media Technology ◽  
Factors Affecting ◽  
Media Usage ◽  
Internal Operations ◽  
Use Of Social Media ◽  
The Impact

Utilization of social media technology for business interests has been widely done both in largecompanies and MSMEs (Micro, Small and Medium Enterprise). Utilization of social media forMSMEs is very important to face the competition in this globalization era. This study empiricallyexamines the antecedents of social media usage and its impact on MSMEs performance basedon the Technology-Organization-Environment framework and Resource Based View theory. Thesurvey method by distributing questionnaires was conducted to MSMEs from various industriesin Magelang. Analysis with SEM-Partial Least Square indicates that customer pressure andmobile environment are significant factors affecting the use of social media. Furthermore, thedimensions of the impact on internal operations, sales, marketing and customer service aresignificant and make the value of social media usage for MSMEs. Technological competenceand competitive pressure does not affect the social media usage for MSMEs.Keywords: social media, SMEs, organization perspective, TOE, RBV

scholarly journals Decision making by NICE: examining the influences of evidence, process and context

2013 ◽  
Vol 9 (2) ◽  
pp. 119-141 ◽  
Author(s):  
Karin H. Cerri ◽  
Martin Knapp ◽  
Jose-Luis Fernandez
Keyword(s):  
Decision Making ◽  
New Technologies ◽  
Multinomial Logistic Regression ◽  
Clinical Excellence ◽  
Outcome Variable ◽  
Data Set ◽  
Factors Affecting ◽  
Explanatory Variables ◽  
Relative Contribution ◽  
The Impact

AbstractThe National Institute for Health and Clinical Excellence (NICE) provides guidance to the National Health Service (NHS) in England and Wales on funding and use of new technologies. This study examined the impact of evidence, process and context factors on NICE decisions in 2004–2009. A data set of NICE decisions pertaining to pharmaceutical technologies was created, including 32 variables extracted from published information. A three-category outcome variable was used, defined as the decision to ‘recommend’, ‘restrict’ or ‘not recommend’ a technology. With multinomial logistic regression, the relative contribution of explanatory variables on NICE decisions was assessed. A total of 65 technology appraisals (118 technologies) were analysed. Of the technologies, 27% were recommended, 58% were restricted and 14% were not recommended by NICE for NHS funding. The multinomial model showed significant associations (p ⩽ 0.10) between NICE outcome and four variables: (i) demonstration of statistical superiority of the primary endpoint in clinical trials by the appraised technology; (ii) the incremental cost-effectiveness ratio (ICER); (iii) the number of pharmaceuticals appraised within the same appraisal; and (iv) the appraisal year. Results confirm the value of a comprehensive and multivariate approach to understanding NICE decision making. New factors affecting NICE decision making were identified, including the effect of clinical superiority, and the effect of process and socio-economic factors.

scholarly journals Eksistensi gosip di media sosial dalam menentukan return saham di bursa efek indonesia dan persistensi pengaruhnya bersama hari bursa

2017 ◽  
Vol 22 (2) ◽  
Author(s):  
Sawidji Widoatmodjo ◽  
Halim Putera Siswanto
Keyword(s):  
Social Media ◽  
Stock Return ◽  
Control Variable ◽  
Abnormal Returns ◽  
Mailing List ◽  
January Effect ◽  
The Internet ◽  
Message Board ◽  
Noise Traders ◽  
The Impact

It isn’t easy to define whether a stock return is determined by a certain factor or trading days. There were many research evidence that some factors had influenced stock return. There were also, however, many researches on stock return anomaly providing the facts that stock return, especially their abnormal returns, were caused by specific trading days, such as week-day effect, January effect, and many others. This research attempts to explore this logic. We tested the impact of gossips that spreaded-out through social media, as a certain factor, and all trading days in a week to a stock return. We used the gossips in social media as response of the massive use of the internet in stock investment. The existence of the gossips is more strengthened by the existence of noise traders. Nowadays, noise traders use the internet, such as mailing list, message board, facebook, and others, that are called as social media, as a media to spread gossips. This research investigates whether gossips spreaded through mailing list have a role in mispricing, so then it can be used to determine the stock return. If they have the role, then how long is the persistence? To anticipate the impact of trading days, this research also includes trading days as a control variable. Using multivariate statistical technique and combined with event study with five windows (five days before and after a gossip has been posted), this research analyzes the stock return that gets the most gossips posted by investors. The result suggests that the gossips in social media don’t show significant influence on the stock return, and automatically no persistence exists. Based on that result, the conclusion is that the gossips in social media can’t be used to determine the stock return. The implication is that even social media can facilitate the stock transaction better, the investors in Indonesia Stock Exchange can’t exploit the gossips in social media for taking profit through behaving as noise traders.

scholarly journals The functional shift in social media; prepositions and conjunction as a sample: الانزياح الوظيفي في مواقع التواصل الاجتماعي "حروف الجر والعطف أنموذجا"

2019 ◽  
Vol 5 (4) ◽  
Author(s):  
NUJUD ISMAIL ALANAZI, MOHD AZIDAN ABDUL JABAR, ABDURRAUF HAS
Keyword(s):  
Social Media ◽  
Arab World ◽  
Arabic Language ◽  
Study Data ◽  
Third Party ◽  
Factors Affecting ◽  
Social Events ◽  
The People ◽  
Functional Shift ◽  
The Impact

  Arabic language is exposed to many negative linguistic manifestations, such as the phenomenon of widespread grammatical error in social media. The aim of the current study is to monitor grammatical errorin in social media and to identify factors affecting mistakes for (prepositions, conjunctions). The study also seeks to investigate the impact of grammatical variation on the understanding and to detect the effect of grammatical erroron Level. In order to verify the validity of the hypotheses and to answer all the questions, the researcher used the statistical analytical descriptive method in order to obtain the study data. invention “Application third party” by the researcher to correct mistakes among people in social media. The study sample consist of only 200 sentences from (2016 to 2018). with many Arab political and social events occurring in this period, so the social media has become an important and influential medium in the Arab world. The main of results of research was descriptive and statistical results: The Mistake was just in conjunctions, prepositions; because the people used it misplaced. The mistake in the prepositions were %82, while the mistake in the conjunctions just %17.    

scholarly journals The common grammatical error in name among the Arab Twittered in Twitter: العدول النحوي الشائع في الاسم بين المغردين العرب في تويتر

2019 ◽  
Vol 3 (3) ◽  
Author(s):  
Nujood Ismail Rafie Al Anzi - Mohammed Azidan Abdul Jabbar
Keyword(s):  
Social Media ◽  
Arab World ◽  
Study Data ◽  
Factors Affecting ◽  
Social Events ◽  
Grammatical Variation ◽  
Grammatical Error ◽  
The Common ◽  
The Impact ◽  
Descriptive Method

 Arabic is exposed to many negative linguistic manifestations, such as the phenomenon of widespread grammatical errorin social media, especially Twitter. The aim of the current study is to monitor grammatical errorin Twitter tweets and to identify factors affecting grammatical errorin Twitter tweets. The study also seeks to investigate the impact of grammatical variation on the understanding of tweets and to detect the effect of grammatical erroron Level level. In order to verify the validity of the hypotheses and to answer all the questions, the researcher will use the statistical analytical descriptive method in order to obtain the study data. The study will then devise a computer program designed by the researcher to correct common grammatical error among Twitter. The study sample will consist of only 200 informative tweets from 2016 to 2018, with many Arab political and social events occurring in this period, so Twitter has become an important and influential medium in the Arab world. The nature of the research requires that it be in four chapters, preceded by an introduction and followed by a conclusion.

scholarly journals Travel and us: The impact of mode share on sentiment using geo-social media and GIS

2021 ◽  
Author(s):  
Greg Rybarczyk ◽  
Syagnik Banerjee ◽  
Melissa D. Starking-Szymanski ◽  
Richard Ross Shaker
Keyword(s):  
Social Media ◽  
Spatial Data ◽  
Spatial Regression ◽  
Negative Influence ◽  
Spatial Data Analysis ◽  
Spatial Autoregression ◽  
Spatial Error ◽  
Factors Affecting ◽  
Pedestrian Travel ◽  
The Impact

Commute stress is a serious health problem that impacts nearly everyone. Considering that microblogged geo-locational information offers new insight into human attitudes, the present research examined the utility of geo-social media data for understanding how different active and inactive travel modes affect feelings of pleasure, or displeasure, in two major U.S. cities: Chicago, Illinois and Washington D.C. A popular approach was used to derive a sentiment index (pleasure or valence) for each travel Tweet. Methodologically, exploratory spatial data analysis (ESDA) and global and spatial regression models were used to examine the geography of all travel modes and factors affecting their valence. After adjusting for spatial error associated with socioeconomic, environmental, weather, and temporal factors, spatial autoregression models proved superior to the base global model. The results showed that water and pedestrian travel were universally associated with positive valences. Bicycling also favorably influenced valence, albeit only in D.C. A noteworthy finding was the negative influence temperature and humidity had on valence. The outcomes from this research should be considered when additional evidence is needed to elevate commuter sentiment values in practice and policy, especially in regards to active transportation.

scholarly journals Travel and us: The impact of mode share on sentiment using geo-social media and GIS

2021 ◽  
Author(s):  
Greg Rybarczyk ◽  
Syagnik Banerjee ◽  
Melissa D. Starking-Szymanski ◽  
Richard Ross Shaker
Keyword(s):  
Social Media ◽  
Spatial Data ◽  
Spatial Regression ◽  
Negative Influence ◽  
Spatial Data Analysis ◽  
Spatial Autoregression ◽  
Spatial Error ◽  
Factors Affecting ◽  
Pedestrian Travel ◽  
The Impact

Commute stress is a serious health problem that impacts nearly everyone. Considering that microblogged geo-locational information offers new insight into human attitudes, the present research examined the utility of geo-social media data for understanding how different active and inactive travel modes affect feelings of pleasure, or displeasure, in two major U.S. cities: Chicago, Illinois and Washington D.C. A popular approach was used to derive a sentiment index (pleasure or valence) for each travel Tweet. Methodologically, exploratory spatial data analysis (ESDA) and global and spatial regression models were used to examine the geography of all travel modes and factors affecting their valence. After adjusting for spatial error associated with socioeconomic, environmental, weather, and temporal factors, spatial autoregression models proved superior to the base global model. The results showed that water and pedestrian travel were universally associated with positive valences. Bicycling also favorably influenced valence, albeit only in D.C. A noteworthy finding was the negative influence temperature and humidity had on valence. The outcomes from this research should be considered when additional evidence is needed to elevate commuter sentiment values in practice and policy, especially in regards to active transportation.

Impact of Agriculture Factor and Non-Agriculture Factor to Value of Food Production: Cast Study of Vietnam, Thailand, Indonesia and Philippines Period 2010-2019

2021 ◽  
Vol 1 (2) ◽  
pp. 80
Author(s):  
Muhamad Ferdy Firmansyah ◽  
Dewi Pratiwi Pusparini ◽  
Arriane A. Vivero ◽  
Neldren Grace Lababit
Keyword(s):  
Food Production ◽  
Control Variable ◽  
Value Added ◽  
Secondary Data ◽  
Political Stability ◽  
The Philippines ◽  
Factors Affecting ◽  
Average Value ◽  
Agriculture Sector ◽  
Annual Population

Food production provides an overview of developing a country's agriculture resilience and food security. Several factors can affect food production. They can be divided into agriculture factors and non-agriculture factors. This research aims to find agricultural and non-agricultural factors affecting food production. We assume the food production with a used average value of food production. A quantitative approach using a panel data model approach using for this research. The data used is secondary data. The results are that the factors that can affect food production with a used average value of food production are dependent variables. In this research, we used independent variables as follows agriculture land are, agriculture value-added, employment in the agriculture sector, credit to agriculture, and control variable. Control variables used in this research are annual population, gross domestic product, and political stability. This research is based on Vietnam, Thailand, Indonesia, and the Philippines. We used data panel regression for estimating the model, the data period used is in the period 2010-2019. This study provides recommendations that in increasing the optimization of food production, it is necessary to plan for value-added, empower workers, suppress population growth, and political stability.

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