Abstract: As the advancement of technology, online shopping channel develops rapidly in recent years. According to the report of Taiwan Network Information Center, there are almost eighty percents of internet population shopping in online channel. Synthesizing insights from the previous research, this study develops the conceptual model to integrate Theory of Perceived Risk (TPR) and Technology Acceptance Model (TAM) to apply in online shopping. Using data collected from 637 respondents from online survey website, we use structural equation modeling to test measurement and structural models. The results suggest the need for consideration of perceived risk as an antecedent in the Technology Acceptance Model. The limitations and implications are discussed.
Abstract: At the end of the 17th Century the Greek orthodox
Archbishop in Venice -Meletios Typaldos- decided to turn the
doctrine of the orthodox Greeks into Catholicism. More than 5.000
Greeks were living in Venice then. Their leadership -the Greek
confraternity- fought against Meletios. Participants in this conflict
were the Pope, the ecumenical Patriarch in Constantinople and Peter
the Great of Russia. All the play according to my opinion -which is
followed by evidence and theoretical support is a strong conflict
between the two actors -the Archbishop and the Confraternity- and
the object of conflict is the change of the Greek orthodox beliefs to
Catholicism. Ethnicity especially for Greeks of the era is identified
with orthodoxy. So this was a conflict of identity. The results of that
conflict were of tremendous importance to the Greeks in Venice and
affected them for long.
Abstract: The underground shopping mall has the constructional
problem of the fire evacuation. Also, the people sometimes lose their
direction and information of current time in the mall. If the
emergencies such as terrorist explosions or gas explosions are
happened, they have to go out soon. Under such circumstances, inside
of the mall has high risk for life. In this research, the authors propose a
way that he/she can go out from the underground shopping mall
quickly. If the narrow exits are discovered by using active RFID
(Radio Frequency Identification) tags and using cellular phones, they
can evacuate as soon as possible. To verify this hypothesis, the authors
design the model and carry out the agent-based simulation. They treat,
as a case study, the Tenjin mall in Fukuoka Prefecture in Japan. The
result of the simulation is that the case of the pedestrian with using
active RFID tags and cellular phones reduced the amount of time to
spend on the evacuation. Even if the diffusion of RFID tags and
cellular phones was not perfect, they could show the effectiveness of
reducing the time of evacuation.
Abstract: A procedure commonly used in Job Shop Scheduling Problem (JSSP) to evaluate the neighborhoods functions that use the non-deterministic algorithms is the calculation of the critical path in a digraph. This paper presents an experimental study of the cost of computation that exists when the calculation of the critical path in the solution for instances in which a JSSP of large size is involved. The results indicate that if the critical path is use in order to generate neighborhoods in the meta-heuristics that are used in JSSP, an elevated cost of computation exists in spite of the fact that the calculation of the critical path in any digraph is of polynomial complexity.
Abstract: Consider a mass production of HDD arms where
hundreds of CNC machines are used to manufacturer the HDD arms.
According to an overwhelming number of machines and models of
arm, construction of separate control chart for monitoring each HDD
arm model by each machine is not feasible. This research proposed a
strategy to optimize the SPC management on shop floor. The
procedure started from identifying the clusters of the machine with
similar manufacturing performance using clustering technique. The
three way control chart ( I - MR - R ) is then applied to each
clustered group of machine. This proposed research has
advantageous to the manufacturer in terms of not only better
performance of the SPC but also the quality management paradigm.
Abstract: This study aims to identify cellular phone users- shopping motivating factors towards online shopping. 100 university students located in Klang Valley, Malaysia were involved as the respondents. They were required to complete a set of questionnaire and had to own a cellular phone in order to be selected as sample in this study. Three from five proposed hypotheses were supported: purchasing information, shopping utilities and service quality. As a result, marketers and retailers should concentrate more on the less important factors in order to encourage and create willingness of the consumers to purchase online. Recommendation for future research is also presented.
Abstract: People detection from images has a variety of applications such as video surveillance and driver assistance system, but is still a challenging task and more difficult in crowded environments such as shopping malls in which occlusion of lower parts of human body often occurs. Lack of the full-body information requires more effective features than common features such as HOG. In this paper, new features are introduced that exploits global self-symmetry (GSS) characteristic in head-shoulder patterns. The features encode the similarity or difference of color histograms and oriented gradient histograms between two vertically symmetric blocks. The domain-specific features are rapid to compute from the integral images in Viola-Jones cascade-of-rejecters framework. The proposed features are evaluated with our own head-shoulder dataset that, in part, consists of a well-known INRIA pedestrian dataset. Experimental results show that the GSS features are effective in reduction of false alarmsmarginally and the gradient GSS features are preferred more often than the color GSS ones in the feature selection.
Abstract: In the paper we discuss the influence of the route
flexibility degree, the open rate of operations and the production type
coefficient on makespan. The flexible job-open shop scheduling
problem FJOSP (an extension of the classical job shop scheduling) is
analyzed. For the analysis of the production process we used a
hybrid heuristic of the GRASP (greedy randomized adaptive search
procedure) with simulated annealing algorithm. Experiments with
different levels of factors have been considered and compared. The
GRASP+SA algorithm has been tested and illustrated with results for
the serial route and the parallel one.
Abstract: This study attempts to validate the consumer-oriented
criteria list, developed by Wang et al. (2010), for selecting online
travel shopping sites. Based on a sample of 985 respondents,
confirmatory factor analysis was employed to test the factor structure
and assess the reliability and validity of the list. The results support the
list developed by Wang et al. (2010) and claim the list can be further
used to analyze, explain, and understand consumer behaviors about
online travel shopping.
Abstract: The availability of broadband internet and increased
access to computers has been instrumental in the rise of internet
literacy in Malaysia. This development has led to the adoption of
online shopping by many Malaysians. On another note, the
Government has supported the development and production of local
herbal products. This has resulted in an increase in the production and
diversity of products by SMEs. The purpose of this study is to
evaluate the influence of the Malaysian demographic factors and
selected attitudinal characteristics in relation to the online purchasing
of herbal products. In total, 1054 internet users were interviewed
online and Chi-square analysis was used to determine the relationship
between demographic variables and different aspects of online
shopping for herbal products. The overall results show that the
demographic variables such as age, gender, education level, income
and ethnicity were significant when considering the online shopping
antecedents of trust, quality of herbal products, perceived risks and
perceived benefits.
Abstract: Web sites are rapidly becoming the preferred media
choice for our daily works such as information search, company
presentation, shopping, and so on. At the same time, we live in a
period where visual appearances play an increasingly important
role in our daily life. In spite of designers- effort to develop a web
site which be both user-friendly and attractive, it would be difficult
to ensure the outcome-s aesthetic quality, since the visual
appearance is a matter of an individual self perception and opinion.
In this study, it is attempted to develop an automatic system for
web pages aesthetic evaluation which are the building blocks of
web sites. Based on the image processing techniques and artificial
neural networks, the proposed method would be able to categorize
the input web page according to its visual appearance and aesthetic
quality. The employed features are multiscale/multidirectional
textural and perceptual color properties of the web pages, fed to
perceptron ANN which has been trained as the evaluator. The
method is tested using university web sites and the results
suggested that it would perform well in the web page aesthetic
evaluation tasks with around 90% correct categorization.
Abstract: In this paper, mathematical models for permutation flow shop scheduling and job shop scheduling problems are proposed. The first problem is based on a mixed integer programming model. As the problem is NP-complete, this model can only be used for smaller instances where an optimal solution can be computed. For large instances, another model is proposed which is suitable for solving the problem by stochastic heuristic methods. For the job shop scheduling problem, a mathematical model and its main representation schemes are presented.
Abstract: This paper was aimed to survey the level of awareness
of traditional grocery stores in Bangkok in these categories: location,
service quality, risk, shopping, worthwhile, shopping satisfaction, and
future shopping intention. The paper was also aimed to survey factors
influencing the decision to shop at traditional grocery stores in
Bangkok in the future. The findings revealed that consumers had a
high level of awareness of traditional grocery stores in Bangkok.
Consumers were aware that the price was higher and it was riskier to
buy goods and services at traditional grocery stores but they still had
a high level of preference to patronage traditional grocery stores. This
was due to the reasons that there was a high level of satisfaction from
the factors of the friendliness of the owner, the ability to negotiate the
price, the ability to buy on credit, free delivery, and the enjoyment to
meet with other customers in the same neighborhood.
Abstract: The job shop scheduling problem (JSSP) is a
notoriously difficult problem in combinatorial optimization. This
paper presents a hybrid artificial immune system for the JSSP with the
objective of minimizing makespan. The proposed approach combines
the artificial immune system, which has a powerful global exploration
capability, with the local search method, which can exploit the optimal
antibody. The antibody coding scheme is based on the operation based
representation. The decoding procedure limits the search space to the
set of full active schedules. In each generation, a local search heuristic
based on the neighborhood structure proposed by Nowicki and
Smutnicki is applied to improve the solutions. The approach is tested
on 43 benchmark problems taken from the literature and compared
with other approaches. The computation results validate the
effectiveness of the proposed algorithm.
Abstract: During last decades, developing multi-objective
evolutionary algorithms for optimization problems has found
considerable attention. Flexible job shop scheduling problem, as an
important scheduling optimization problem, has found this attention
too. However, most of the multi-objective algorithms that are
developed for this problem use nonprofessional approaches. In
another words, most of them combine their objectives and then solve
multi-objective problem through single objective approaches. Of
course, except some scarce researches that uses Pareto-based
algorithms. Therefore, in this paper, a new Pareto-based algorithm
called controlled elitism non-dominated sorting genetic algorithm
(CENSGA) is proposed for the multi-objective FJSP (MOFJSP). Our
considered objectives are makespan, critical machine work load, and
total work load of machines. The proposed algorithm is also
compared with one the best Pareto-based algorithms of the literature
on some multi-objective criteria, statistically.
Abstract: Having done in this study, air-conditioning
automation for patisserie shopwindow was designed. In the cooling
sector it is quite important to cooling up the air temperature in the
shopwindow within short time interval. Otherwise the patisseries
inside of the shopwindow will be spoilt in a few days. Additionally
the humidity is other important parameter for the patisseries kept in
shopwindow. It must be raised up to desired level in a quite short
time. Traditional patisserie shopwindows only allow controlling
temperature manually. There is no humidity control and humidity is
supplied by fans that are directed to the water at the bottom of the
shopwindows. In this study, humidity and temperature sensors
(SHT11), PIC, AC motor controller, DC motor controller, ultrasonic
nebulizer and other electronic circuit members were used to simulate
air conditioning automation for patisserie shopwindow in proteus
software package. The simulation results showed that temperature
and humidity values are adjusted in desired time duration by openloop
control technique. Outer and inner temperature and humidity
values were used for control mechanism.
Abstract: The purpose of the study was to investigate the
effectiveness of ICT training workshop of tutors of Allama Iqbal
Open University Pakistan. The study was delimited to tutors of
Multan region. The total sample comprised of 100 tutors. All the
tutors who participated in ICT training workshop in Multan region
were taken as sample in the study. A questionnaire having two parts,
based on five point rating scale was developed by the researcher. Part
one was about the competency level of computer skills while Part
two was based on items related to training delivery, structure and
content. Part One of questionnaire had five levels of competency
about computer skills. The questionnaire was personally administered
and collected back by the researcher himself on the last day of
workshop.
The collected data were analyzed by using descriptive statistics.
Through this study it was found that majority of the tutors strongly
agreed that training enhanced their computer skills. Majority of the
respondents consider themselves to be generally competent in the use
of computer. They also agreed that there was appropriate
infrastructure and technical support in lab during training workshop.
Moreover, it was found that the training imparted the knowledge of
pedagogy of using computers for distance education.
Abstract: Knowing about the customer behavior in a grocery has
been a long-standing issue in the retailing industry. The advent of
RFID has made it easier to collect moving data for an individual
shopper's behavior. Most of the previous studies used the traditional
statistical clustering technique to find the major characteristics of
customer behavior, especially shopping path. However, in using the
clustering technique, due to various spatial constraints in the store,
standard clustering methods are not feasible because moving data such
as the shopping path should be adjusted in advance of the analysis,
which is time-consuming and causes data distortion. To alleviate this
problem, we propose a new approach to spatial pattern clustering
based on the longest common subsequence. Experimental results using
real data obtained from a grocery confirm the good performance of the
proposed method in finding the hot spot, dead spot and major path
patterns of customer movements.
Abstract: Artificial Immune System is applied as a Heuristic
Algorithm for decades. Nevertheless, many of these applications
took advantage of the benefit of this algorithm but seldom proposed
approaches for enhancing the efficiency. In this paper, a
Self-evolving Artificial Immune System is proposed via developing
the T and B cell in Immune System and built a self-evolving
mechanism for the complexities of different problems. In this
research, it focuses on enhancing the efficiency of Clonal selection
which is responsible for producing Affinities to resist the invading of
Antigens. T and B cell are the main mechanisms for Clonal
Selection to produce different combinations of Antibodies.
Therefore, the development of T and B cell will influence the
efficiency of Clonal Selection for searching better solution.
Furthermore, for better cooperation of the two cells, a co-evolutional
strategy is applied to coordinate for more effective productions of
Antibodies. This work finally adopts Flow-shop scheduling
instances in OR-library to validate the proposed algorithm.
Abstract: This paper considers a scheduling problem in flexible
flow shops environment with the aim of minimizing two important
criteria including makespan and cumulative tardiness of jobs. Since
the proposed problem is known as an Np-hard problem in literature,
we have to develop a meta-heuristic to solve it. We considered
general structure of Genetic Algorithm (GA) and developed a new
version of that based on Data Envelopment Analysis (DEA). Two
objective functions assumed as two different inputs for each Decision
Making Unit (DMU). In this paper we focused on efficiency score of
DMUs and efficient frontier concept in DEA technique. After
introducing the method we defined two different scenarios with
considering two types of mutation operator. Also we provided an
experimental design with some computational results to show the
performance of algorithm. The results show that the algorithm
implements in a reasonable time.