Abstract: The production of nanofibers and the machinery for their production is a current issue. The pioneer, in the industrial production of nanofibers, is the machinery with the sales descriptions NanospiderTM from the company Elmarco, which came into being in 2008. Most of the production facilities, like NanospiderTM, use electrospinning. There are also other methods of industrial production of nanofibers, such as the centrifugal spinning process, which is used by FibeRio Technology Corporation. However, each method and machine has its advantages, but also disadvantages and that is the reason why a new machine called as Nanomachine, which eliminates the disadvantages of other production facilities producing nanofibers, has been developed.
Abstract: Knowledge management focuses on the development, storage, retrieval, and dissemination of information and expertise. It has become an important tool to improve performance in tourism enterprises. This includes improving decision-making, developing customer services, and increasing sales and profits. Knowledge management adoption depends on human, organizational and technological factors. This study aims to explore the concept of knowledge management in travel agents in Egypt. It explores the requirements of adoption and its impact on performance in these agencies. The study targets Category A travel agents in Egypt. The population of the study encompasses Category A travel agents having online presence. An online questionnaire is used to collect data from managers of travel agents. This study is useful for travel agents who are in urgent need to restructure their intermediary role and support their survival in the global travel market. The study sheds light on the requirements of adoption and the expected impact on performance. This could help travel agents identify their situation and the determine the extent to which they are ready to adopt knowledge management. This study is contributing to knowledge by providing insights from the tourism sector in a developing country where the concept of knowledge management is still in its infancy stages.
Abstract: This study attempts to consider the linkage between management and computer sciences in order to develop the software named “IntelSymb” as a demo application to prove data analysis of non-energy* fields’ diversification, which will positively influence on energy dependency mitigation of countries. Afterward, we analyzed 18 years of economic fields of development (5 sectors) of 13 countries by identifying which patterns mostly prevailed and which can be dominant in the near future. To make our analysis solid and plausible, as a future work, we suggest developing a gateway or interface, which will be connected to all available on-line data bases (WB, UN, OECD, U.S. EIA) for countries’ analysis by fields. Sample data consists of energy (TPES and energy import indicators) and non-energy industries’ (Main Science and Technology Indicator, Internet user index, and Sales and Production indicators) statistics from 13 OECD countries over 18 years (1995-2012). Our results show that the diversification of non-energy industries can have a positive effect on energy sector dependency (energy consumption and import dependence on crude oil) deceleration. These results can provide empirical and practical support for energy and non-energy industries diversification’ policies, such as the promoting of Information and Communication Technologies (ICTs), services and innovative technologies efficiency and management, in other OECD and non-OECD member states with similar energy utilization patterns and policies. Industries, including the ICT sector, generate around 4 percent of total GHG, but this is much higher — around 14 percent — if indirect energy use is included. The ICT sector itself (excluding the broadcasting sector) contributes approximately 2 percent of global GHG emissions, at just under 1 gigatonne of carbon dioxide equivalent (GtCO2eq). Ergo, this can be a good example and lesson for countries which are dependent and independent on energy, and mainly emerging oil-based economies, as well as to motivate non-energy industries diversification in order to be ready to energy crisis and to be able to face any economic crisis as well.
Abstract: This study aims to investigate the impact of data leak of M&S customers on digital communities. Modern businesses are using digital communities as an important public relations tool for marketing purposes. This form of communication helps companies to build better relationship with their customers which also act as another source of information. The communication between the customers and the organizations is not regulated so users may post positive and negative comments. There are new platforms being developed on a daily basis and it is very crucial for the businesses to not only get themselves familiar with those but also know how to reach their existing and perspective consumers. The driving force of marketing and communication in modern businesses is the digital communities and these are continuously increasing and developing. This phenomenon is changing the way marketing is conducted. The current research has discussed the implications on M&S business performance since the data was exploited on digital communities; users contacted M&S and raised the security concerns. M&S closed down its website for few hours to try to resolve the issue. The next day M&S made a public apology about this incidence. This information was proliferated on various digital communities and it has impacted negatively on M&S brand name, sales and customers. The content analysis approach is being used to collect qualitative data from 100 digital bloggers including social media communities such as Facebook and Twitter. The results and finding provide useful new insights into the nature and form of security concerns of digital users. Findings have theoretical and practical implications. This research will showcase a large corporation utilizing various digital community platforms and can serve as a model for future organizations.
Abstract: Nowadays, education cannot be imagined without digital technologies. It broadens the horizons of teaching learning processes. Several universities are offering online courses. For evaluation purpose, e-examination systems are being widely adopted in academic environments. Multiple-choice tests are extremely popular. Moving away from traditional examinations to e-examination, Moodle as Learning Management Systems (LMS) is being used. Moodle logs every click that students make for attempting and navigational purposes in e-examination. Data mining has been applied in various domains including retail sales, bioinformatics. In recent years, there has been increasing interest in the use of data mining in e-learning environment. It has been applied to discover, extract, and evaluate parameters related to student’s learning performance. The combination of data mining and e-learning is still in its babyhood. Log data generated by the students during online examination can be used to discover knowledge with the help of data mining techniques. In web based applications, number of right and wrong answers of the test result is not sufficient to assess and evaluate the student’s performance. So, assessment techniques must be intelligent enough. If student cannot answer the question asked by the instructor then some easier question can be asked. Otherwise, more difficult question can be post on similar topic. To do so, it is necessary to identify difficulty level of the questions. Proposed work concentrate on the same issue. Data mining techniques in specific clustering is used in this work. This method decide difficulty levels of the question and categories them as tough, easy or moderate and later this will be served to the desire students based on their performance. Proposed experiment categories the question set and also group the students based on their performance in examination. This will help the instructor to guide the students more specifically. In short mined knowledge helps to support, guide, facilitate and enhance learning as a whole.
Abstract: The present study aims to explore the effect of
computerization on marketing performance in Snowa Company. In
other words, this study intends to respond to this question that
whether or not, is there any relationship between utilization of
computerization in marketing activities and marketing performance?
The statistical population included 60 marketing managers of Snowa
Company. In order to test the research hypotheses, Pearson
correlation coefficient was employed. The reliability was equal to
96.8%. In this study, computerization was the independent variable
and marketing performance was the dependent variable with
characteristics of market share, improving the competitive position,
and sales volume. The results of testing the hypotheses revealed that
there is a significant relationship between utilization of
computerization and market share, sales volume and improving the
competitive position.
Abstract: Selling has changed. Selling has taken on aspects of
relationship marketing and sales force play a critical role in
developing long-term relationships between buyers and sellers which
is seen to serve the company’s targets and create success for a long
run. The purpose of this study was to examine what really matters in
buyer-seller encounters and determine what expectations business
buyers have. We studied 17 business buyers by a qualitative
interview. We found that buyers appreciate encounters where the
salesperson face the buyer as a way he or she is as a person, map the
real needs to improve buyers’ business and build up cooperation for
long-term relationship. This study show that personality matters are a
key elements when satisfying business buyers’ expectations.
Abstract: The article includes the results and conclusions from
empirical researches that had been done. The research focuses on the
impact of investments made in small and medium-sized enterprises
financed from EU funds on the competitiveness of these companies.
The researches includes financial results in sales revenue and net
income, expenses, and many other new products/services on offer,
higher quality products and services, more modern methods of
production, innovation in management processes, increase in the
number of customers, increase in market share, increase in
profitability of production and provision of services. The main
conclusions are that, companies with direct investments under this
measure shall apply the modern methods of production. The
consequence of this is to increase the quality of our products and
services. Furthermore, both small and medium-sized enterprises have
introduced new products and services. Investments were carried out,
thus enabling better work organization in enterprises. Entrepreneurs
would guarantee higher quality of service, which would result in
better relationships with their customers, what is more, noting the rise
in number of clients. More than half of the companies indicated that
the investments contributed to the increase in market share. Same
thing as for market reach and brand recognition of particular
company. An interesting finding is that, investments in small
enterprises were more effective than medium-sized enterprises.
Abstract: The objective of this study was to evaluate the
effects of calving season on the production and economic efficiency
of dairy farms in Egypt. Our study was performed at dairy
production farms in the Alexandria, Behera, and Kafr El-Sheikh
provinces of Egypt from summer 2010 to winter 2013. The
randomly selected dairy farms had herds consisting of Baladi,
Holstein-Friesian, or cross-bred (Baladi × Holstein-Friesian) cows.
The data were collected from production records and responses to a
structured questionnaire. The average total return differed
significantly (P < 0.05) between the different cattle breeds and
calving seasons. The average total return was highest for the
Holstein- Friesian cows that calved in the winter (29106.42
EGP/cow/year), and it was lowest for Baladi cows that calved in the
summer (12489.79 EGP/cow/year). Differences in total returns
between the cows that calved in the winter or summer or between
the foreign and native breeds, as well as variations in calf prices,
might have contributed to the differences in milk yield. The average
net profit per cow differed significantly (P < 0.05) between the cattle
breeds and calving seasons. The average net profit values for the
Baladi cows that calved in the winter or summer were 2413 and
2994.96 EGP/cow/year, respectively, and those for the Holstein-
Friesian cows were 10744.17 and 7860.56 EGP/cow/year,
respectively, whereas those for the cross-bred cows were 10174.86
and 7571.33 EGP/cow/year, respectively. The variations in net profit
might have resulted from variation in the availability or price of feed
materials, milk prices, or sales volumes. Our results show that the
breed and calving season of dairy cows significantly affected the
economic efficiency of dairy farms in Egypt. The cows that calved
in the winter produced more milk than those that calved in the
summer, which may have been the result of seasonal influences,
such as temperature, humidity, management practices, and the type
of feed or green fodder available.
Abstract: Accurate forecasting of fresh produce demand is one
the challenges faced by Small Medium Enterprise (SME)
wholesalers. This paper is an attempt to understand the cause for the
high level of variability such as weather, holidays etc., in demand of
SME wholesalers. Therefore, understanding the significance of
unidentified factors may improve the forecasting accuracy. This
paper presents the current literature on the factors used to predict
demand and the existing forecasting techniques of short shelf life
products. It then investigates a variety of internal and external
possible factors, some of which is not used by other researchers in the
demand prediction process. The results presented in this paper are
further analysed using a number of techniques to minimize noise in
the data. For the analysis past sales data (January 2009 to May 2014)
from a UK based SME wholesaler is used and the results presented
are limited to product ‘Milk’ focused on café’s in derby. The
correlation analysis is done to check the dependencies of variability
factor on the actual demand. Further PCA analysis is done to
understand the significance of factors identified using correlation.
The PCA results suggest that the cloud cover, weather summary and
temperature are the most significant factors that can be used in
forecasting the demand. The correlation of the above three factors
increased relative to monthly and becomes more stable compared to
the weekly and daily demand.
Abstract: The purpose of the paper is to estimate the US small
wind turbines market potential and forecast the small wind turbines
sales in the US. The forecasting method is based on the application of
the Bass model and the generalized Bass model of innovations
diffusion under replacement purchases. In the work an exponential
distribution is used for modeling of replacement purchases. Only one
parameter of such distribution is determined by average lifetime of
small wind turbines. The identification of the model parameters is
based on nonlinear regression analysis on the basis of the annual
sales statistics which has been published by the American Wind
Energy Association (AWEA) since 2001 up to 2012. The estimation
of the US average market potential of small wind turbines (for
adoption purchases) without account of price changes is 57080
(confidence interval from 49294 to 64866 at P = 0.95) under average
lifetime of wind turbines 15 years, and 62402 (confidence interval
from 54154 to 70648 at P = 0.95) under average lifetime of wind
turbines 20 years. In the first case the explained variance is 90,7%,
while in the second - 91,8%. The effect of the wind turbines price
changes on their sales was estimated using generalized Bass model.
This required a price forecast. To do this, the polynomial regression
function, which is based on the Berkeley Lab statistics, was used. The
estimation of the US average market potential of small wind turbines
(for adoption purchases) in that case is 42542 (confidence interval
from 32863 to 52221 at P = 0.95) under average lifetime of wind
turbines 15 years, and 47426 (confidence interval from 36092 to
58760 at P = 0.95) under average lifetime of wind turbines 20 years.
In the first case the explained variance is 95,3%, while in the second
– 95,3%.
Abstract: Durian is the flagship fruit of Mindanao and there is
an abundance of several cultivars with many confusing identities/
names.
The project was conducted to develop procedure for reliable and
rapid detection and sorting of durian planting materials. Moreover, it
is also aimed to establish specific genetic or DNA markers for routine
testing and authentication of durian cultivars in question.
The project developed molecular procedures for routine testing.
SSR primers were also screened and identified for their utility in
discriminating durian cultivars collected.
Results of the study showed the following accomplishments:
1. Twenty (29) SSR primers were selected and identified based on
their ability to discriminate durian cultivars,
2. Optimized and established standard procedure for identification
and authentication of Durian cultivars
3. Genetic profile of durian is now available at Biotech Unit
Our results demonstrate the relevance of using molecular
techniques in evaluating and identifying durian clones. The most
polymorphic primers tested in this study could be useful tools for
detecting variation even at the early stage of the plant especially for
commercial purposes. The process developed combines the efficiency
of the microsatellites development process with the optimization of
non-radioactive detection process resulting in a user-friendly protocol
that can be performed in two (2) weeks and easily incorporated into
laboratories about to start microsatellite development projects. This
can be of great importance to extend microsatellite analyses to other
crop species where minimal genetic information is currently
available. With this, the University can now be a service laboratory
for routine testing and authentication of durian clones.
Abstract: This exploratory study gives an overview of the
evolution of the main financial and performance indicators of the
Academic Spin-Off’s and High Growth Academic Spin-Off’s in year
3 and year 6 after its creation in the region of Catalonia in Spain. The
study compares and evaluates results of these different measures of
performance and the degree of success of these companies for each
University.
We found that the average Catalonian Academic Spin-Off is small
and have not achieved the sustainability stage at year 6. On the
contrary, a small group of High Growth Academic Spin-Off’s
exhibits robust performance with high profits in year 6. Our results
support the need to increase selectivity and support for these
companies especially near year 3, because are the ones that will bring
wealth and employment. University role as an investor has rigid
norms and habits that impede an efficient economic return from their
ASO investment.
Universities with high performance on sales and employment in
year 3 not always could sustain this growth in year 6 because their
ASO’s are not profitable. On the contrary, profitable ASO exhibit
superior performance in all measurement indicators in year 6. We
advocate the need of a balanced growth (with profits) as a way to
obtain subsequent continuous growth.
Abstract: Traditional document representation for classification
follows Bag of Words (BoW) approach to represent the term weights.
The conventional method uses the Vector Space Model (VSM) to
exploit the statistical information of terms in the documents and they
fail to address the semantic information as well as order of the terms
present in the documents. Although, the phrase based approach
follows the order of the terms present in the documents rather than
semantics behind the word. Therefore, a semantic concept based
approach is used in this paper for enhancing the semantics by
incorporating the ontology information. In this paper a novel method
is proposed to forecast the intraday stock market price directional
movement based on the sentiments from Twitter and money control
news articles. The stock market forecasting is a very difficult and
highly complicated task because it is affected by many factors such
as economic conditions, political events and investor’s sentiment etc.
The stock market series are generally dynamic, nonparametric, noisy
and chaotic by nature. The sentiment analysis along with wisdom of
crowds can automatically compute the collective intelligence of
future performance in many areas like stock market, box office sales
and election outcomes. The proposed method utilizes collective
sentiments for stock market to predict the stock price directional
movements. The collective sentiments in the above social media have
powerful prediction on the stock price directional movements as
up/down by using Granger Causality test.
Abstract: The value co-creation has gained much attention in
sales research, but less is known about how salespeople and
customers interact in the authentic business to business (B2B) sales
meetings. The study presented in this paper empirically contributes to
existing research by presenting authentic B2B sales meetings that
were video recorded and analyzed using observation and qualitative
content analysis methods. This paper aims to study key elements of
successful sales interactions between salespeople and customers/
buyers. This study points out that salespeople are selling value rather
than the products or services themselves, which are only enablers in
realizing business benefits. Therefore, our findings suggest that
promoting and easing open discourse is an essential part of a
successful sales encounter. A better understanding of how
salespeople and customers successfully interact would help
salespeople to develop their interpersonal sales skills.
Abstract: Since the initial creation of the Barbie doll in 1959, it
became a symbol of US society. Likewise, the Licca-chan, a Japanese
doll created in 1967, also became a Japanese symbolic doll of Japanese
society. Prior to the introduction of Licca-chan, Barbie was already
marketed in Japan but their sales were dismal. Licca-chan (an actual
name: Kayama Licca) is a plastic doll with a variety of sizes ranging
from 21.0 cm to 29.0 cm which many Japanese girls dream of having.
For over 35 years, the manufacturer, Takara Co., Ltd. has sold over 48
million dolls and has produced doll houses, accessories, clothes, and
Licca-chan video games for the Nintendo DS. Many First-generation
Licca-chan consumers still are enamored with Licca-chan, and go to
Licca-chan House, in an amusement park with their daughters. These
people are called Licca-chan maniacs, as they enjoy touring the
Licca-chan’s factory in Tohoku or purchase various Licca-chan
accessories. After the successful launch of Licca-chan into the
Japanese market, a mixed-like doll from the US and Japan, a doll,
JeNny, was later sold in the same Japanese market by Takara Co., Ltd.
in 1982.
Comparison of these cultural iconic dolls, Barbie and Licca-chan,
are analyzed in this paper. In fact, these dolls have concepts of girls’
dreams. By using concepts of mythology of Jean Baudrillard, these
dolls can be represented idealized images of figures in the products for
consumers, but at the same time, consumers can see products with
different perspectives, which can cause controversy.
Abstract: Since “Hello Kitty” was manufactured in the market in
1974, the manufacturer, Sanrio Co., Ltd. gains high profits not only
Kitty’s products but also Kitty license, which gives us a picture of
Sanrio’s sales strategy in the global market. Kitty’s history, its
products, and Sanrio’s sales strategy are researched in this paper.
Comparing it to American Girl, and focusing on KITTYLAB, a type of
attraction where you can enjoy games with Kitty, and choose its parts
to build your own Kitty, the image of the cultural icon can be altered.
Abstract: Chemical Reaction Optimization (CRO) is an
optimization metaheuristic inspired by the nature of chemical
reactions as a natural process of transforming the substances from
unstable to stable states. Starting with some unstable molecules with
excessive energy, a sequence of interactions takes the set to a state of
minimum energy. Researchers reported successful application of the
algorithm in solving some engineering problems, like the quadratic
assignment problem, with superior performance when compared with
other optimization algorithms. We adapted this optimization
algorithm to the Printed Circuit Board Drilling Problem (PCBDP)
towards reducing the drilling time and hence improving the PCB
manufacturing throughput. Although the PCBDP can be viewed as
instance of the popular Traveling Salesman Problem (TSP), it has
some characteristics that would require special attention to the
transactions that explore the solution landscape. Experimental test
results using the standard CROToolBox are not promising for
practically sized problems, while it could find optimal solutions for
artificial problems and small benchmarks as a proof of concept.
Abstract: e-Service has moved from the usual manual and
traditional way of rendering services to electronic service provision
for the public and there are several reasons for implementing these
services, Airline ticketing have gone from its manual traditional way
to an intelligent web-driven service of purchasing. Many companies
have seen their profits doubled through the use of online services in
their operation and a typical example is Hewlett Packard (HP) which
is rapidly transforming their after sales business into a profit
generating e-service business unit.
This paper will examine the various challenges confronting e-
Service adoption and implementation in Nigeria and also analyse
lessons learnt from e-Service adoption and implementation in Asia to
see how it could be useful in Nigeria which is a lower middle income
country. From the analysis of the online survey data, it has been
identified that the public in Nigeria are much aware of e-Services but
successful adoption and implementation have been the problems
faced.
Abstract: Innovations not only contribute to competitiveness of
the company but have also positive effects on revenues. On average,
product innovations account to 14 percent of companies’ sales.
Innovation management has substantially changed during the last
decade, because of growing reliance on external partners. As a
consequence, a new task for purchasing arises, as firms need to
understand which suppliers actually do have high potential
contributing to the innovativeness of the firm and which do not.
Proper organization of the purchasing function is important since
for the majority of manufacturing companies deal with substantial
material costs which pass through the purchasing function. In the past
the purchasing function was largely seen as a transaction-oriented,
clerical function but today purchasing is the intermediate with supply
chain partners contributing to innovations, be it product or process
innovations. Therefore, purchasing function has to be organized
differently to enable firm innovation potential.
However, innovations are inherently risky. There are behavioral
risk (that some partner will take advantage of the other party),
technological risk in terms of complexity of products and processes
of manufacturing and incoming materials and finally market risks,
which in fact judge the value of the innovation. These risks are
investigated in this work. Specifically, technological risks which deal
with complexity of the products, and processes will be investigated
more thoroughly. Buying components or such high edge technologies
necessities careful investigation of technical features and therefore is
usually conducted by a team of experts. Therefore it is hypothesized
that higher the technological risk, higher will be the centralization of
the purchasing function as an interface with other supply chain
members.
Main contribution of this research lies is in the fact that analysis
was performed on a large data set of 1493 companies, from 25
countries collected in the GMRG 4 survey. Most analyses of
purchasing function are done by case study analysis of innovative
firms. Therefore this study contributes with empirical evaluations that
can be generalized.