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Delays in Services and Customer Service Evaluation: A Study of Family Dining Restaurants of Pakistan
Maqsood Ahmad,
Hina Naseer
Issue:
Volume 7, Issue 4, August 2018
Pages:
108-116
Received:
26 June 2018
Accepted:
27 July 2018
Published:
17 August 2018
Abstract: Wait management is very important subject in service sectors because people are moving towards services due to globalization and now it has become common phenomena. Dining at restaurants has become a trend in today’s world due to increasing demand of family’s as well as time constraints. In developed countries, there is much focus on service sectors and it is producing half revenues ($1.258 trillion) of countries like USA, UK, and Japan. However, in developing countries, a service sector has not yet generated much revenue because it seems difficult for developing countries to handle it due to different demands and niche of customers. In current study, 400 questionnaires were distributed to respondents and 300 were received back. Data was analyzed using SPSS version 17 and results revealed that if good environment is provided at waiting area of restaurant lobbies, then waiting customer behavior can be managed and consequently customer satisfaction. Our results also revealed that physical environment has a positive relationship with customer satisfaction and when this relationship is checked through mediating variable (customer behavior during wait), it also shows positive relationship. On the contrary, social environment has a negative relationship with customer satisfaction and when this relationship is checked through mediating variable (customer behavior during wait), it also shows negative relationship.
Abstract: Wait management is very important subject in service sectors because people are moving towards services due to globalization and now it has become common phenomena. Dining at restaurants has become a trend in today’s world due to increasing demand of family’s as well as time constraints. In developed countries, there is much focus on service sector...
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A New Stock Selection Model Based on Decision Tree C5.0 Algorithm
Qiansheng Zhang,
Jingru Zhang,
Zisheng Chen,
Miao Zhang,
Songying Li
Issue:
Volume 7, Issue 4, August 2018
Pages:
117-124
Received:
10 August 2018
Accepted:
1 September 2018
Published:
21 September 2018
Abstract: Due to the disordered characteristic and strong randomness of China's stock market, the typical data mining algorithms currently used to analyze and forecast the stock have imprecise prediction outcomes. In order to solve this problem, based on the industry rotation cycle theory, this paper constructs a new stock selection model combining Decision Tree C5.0 Algorithm and factor analysis. Industry rotation cycle theory aims to analyze the development trend of various industries to find promising industries as initial stock pool. According to this principle, this paper selects four industries and the A-share stocks of these industries are used as initial stock pool. This paper builds a stock index system consisting of six effective factors based on the factor analysis of stocks financial indicators and technical indicators. Then Decision Tree C5.0 Algorithm is presented to realize the prediction of stock returns and the classification of stocks. The empirical test of the proposed stock selection model, using the data from the second and the third quarter of 2017 in China A-share stock market, demonstrates that this model has significant difference in the classification accuracy between low-yielding stocks and high-yielding stocks in that case classification accuracy shows a trend opposite against stock return rate. In a conclusion, this model can effectively help investors to avoid risks and make rational investment but has little effect on obtaining excess return.
Abstract: Due to the disordered characteristic and strong randomness of China's stock market, the typical data mining algorithms currently used to analyze and forecast the stock have imprecise prediction outcomes. In order to solve this problem, based on the industry rotation cycle theory, this paper constructs a new stock selection model combining Decision ...
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Determinants of Agricultural Technology Adoption: The Case of Improved Highland Maize Varieties in Toke Kutaye District, Oromia Regional State, Ethiopia
Dawit Milkias,
Abduselam Abdulahi
Issue:
Volume 7, Issue 4, August 2018
Pages:
125-132
Received:
24 June 2018
Accepted:
6 September 2018
Published:
9 October 2018
Abstract: Improved highland Maize is a new and promising crop gradually becoming important in Ethiopian highlands. Its production is rapidly increasing where it has been a minor crop in the past. The empirical evidences on the determinants of agricultural technology adoption and their intensity of adoption are very limited. In this paper, determinants of adoption and intensity of adoption of improved highland maize varieties were investigated by using descriptive statistics and econometric model (Tobit). Two stage sampling procedure was followed in order to draw 150 sample respondents. The model result revealed that variables such as farm size, household income, access to credit, contact with extension agents, participation in training, and field day were positively and significantly influenced whereas, age of household and market distance negatively influenced adoption and intensity of use of improved highland maize varieties in the study area. Therefore, government policies and intervention on adoption and intensity use of agricultural technology should pay attention and move along with those variables significantly influencing adoption and intensity of use of new agricultural technology.
Abstract: Improved highland Maize is a new and promising crop gradually becoming important in Ethiopian highlands. Its production is rapidly increasing where it has been a minor crop in the past. The empirical evidences on the determinants of agricultural technology adoption and their intensity of adoption are very limited. In this paper, determinants of ado...
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