Search results for: customers' behavior

Authors: Rasha Alhendawi

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This research will give the introductory ideas for cultural adaption of B2C E-Service design in Germany. By the intense competition of E-Service development, many companies have realized the importance of understanding the emotional and cultural characteristics of their customers. Ignoring customers’ needs and requirements throughout the E-Service design can lead to faults, mistakes, and gaps. The term of E-Service usability now is changed not only to develop high quality E-Services, but also to be extended to include customer satisfaction and provide for them to feel local.

Keywords: human computer interaction (HCI), usability, cultural usability, E-Services, business-to-consumer (B2C), e-services

Procedia PDF Downloads 410

Authors: Haifeng Wang, Haili Zhang

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Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.

Keywords: computational social science, movie preference, machine learning, SVM

Procedia PDF Downloads 235

Authors: Thachamon Sinsoongsud, Noppawan Piaseu

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This predictive study was aimed to 1) describe self efficacy for risk reduction and preventive behavior for osteoporosis, and 2) examine factors predicting preventive behavior for osteoporosis in nursing students. Through purposive sampling, the sample included 746 nursing students in a public university in Bangkok, Thailand. Data were collected by a self-reported questionnaire on self efficacy and preventive behavior for osteoporosis. Data were analyzed using descriptive statistics and multiple regression analysis with stepwise method. Results revealed that majority of the students were female (98.3%) with mean age of 19.86 + 1.26 years. The students had self efficacy and preventive behavior for osteoporosis at moderate level. Self efficacy and level of education could together predicted 35.2% variance of preventive behavior for osteoporosis (p< .001). Results suggest approaches for promoting preventive behavior for osteoporosis through enhancing self efficacy among nursing students in a public university in Bangkok, Thailand.

Keywords: osteoporosis, self-efficacy, preventive behavior, nursing students

Procedia PDF Downloads 341

Authors: Burcu Oralhan, Zeki Oralhan, Nilsun Sariyer, Kumru Uyar

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Data mining has been becoming more and more important and a wide range of applications in recent years. Data mining is the process of find hidden and unknown patterns in big data. One of the applied fields of data mining is Customer Relationship Management. Understanding the relationships between products and customers is crucial for every business. Customer Relationship Management is an approach to focus on customer relationship development, retention and increase on customer satisfaction. In this study, we made an application of a data mining methods in telecommunication customer relationship management side. This study aims to determine the customers profile who likely to leave the system, develop marketing strategies, and customized campaigns for customers. Data are clustered by applying classification techniques for used to determine the churners. As a result of this study, we will obtain knowledge from international telecommunication industry. We will contribute to the understanding and development of this subject in Customer Relationship Management.

Keywords: customer churn analysis, customer relationship management, data mining, telecommunication industry

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Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

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Advanced metering technologies coupled with informatics creates an opportunity to form digital multi-utility service providers. These providers will be able to concurrently collect a customers’ medium-high resolution water, electricity and gas demand data and provide user-friendly platforms to feed this information back to customers and supply/distribution utility organisations. With the emergence of blockchain technology, a new research area has been explored which helps bring this multi-utility service provider concept to a much higher level. This study aims at introducing a breakthrough system architecture where smart metering technology in water, energy, and gas (WEG) are combined with blockchain technology to provide customer a novel real-time consumption report and decentralized resource trading platform. A pilot study on 4 properties in Australia has been undertaken to demonstrate this system, where benefits for customers and utilities are undeniable.

Keywords: blockchain, digital multi-utility, end use, demand forecasting

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Authors: Siri-Orn Champatong

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This research aimed to study the relationship between attitudes toward marketing mix and customers’ repurchase intention of Thai dessert in case of Ekachai Salee Suphan’s shop in Thailand. This study employed by survey and quantitative research and the questionnaire was used to collect the data from 385 sampled of customers who visited at Ekachai Salee Suphan's shop in Thailand. The descriptive statistics and Pearson’s correlation coefficient analysis was used to analyze data. The research found that the customers’ perception on the overall and individual aspects of attitudes toward marketing mix include products, prices, promotions, and physical characteristics were at very good level, but distribution channels, staffs, and management process were at good level. Furthermore, the hypothesis tests found that attitudes toward overall marketing mix had relationship with individual aspects of intention that were the repurchase intention, willingness to recommend others to repurchase, and possibility to repurchase with statistical significance level of 0.01.

Keywords: intention, repurchase, service marketing mix, Thai dessert

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Authors: Endah Mastuti, Prihastuti Sudaryono

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The rapid development of Internet usage and technology influences the academic behavior of students in high schools. One of the consequences is the emergence of academic procrastination behavior. Academic procrastination behavior is students’ procrastinate behavior in completing assignments. This study aimed to see whether there are differences in the duration of using the internet with academic procrastinate behavior among high school students in Surabaya. The number of research subject is 498 high school students. Instruments of the research are academic procrastination scale and duration of the internet usage questionnaire. The results from One Way Anova shows F value 0.241 with a significance level of 0.868 This demonstrates that there is no difference between the duration of the use of the Internet with academic procrastination behavior in high school students.

Keywords: academic procrastination, duration of internet usage, students, senior high school

Procedia PDF Downloads 326

Authors: Majid Mohammadi, Mohammad Yosef Zadeh, Vahid Naderi Darshori

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The main purpose of this research is concreting of satisfaction literature for obtain index with online content in carmaker industry. The study measures customer satisfaction of online and collect from similar studies with reference to a model of online satisfaction, they are attempting to complete. Statistical communities of research are online customers' carmaker Iran Khodro has been buying the company's products in the last six months. One of the innovative measures in this study is that, customer reviews are obtained through an Internet site. Reliability of the data collected in this study, the Cronbach's alpha coefficient was approved. The coefficient of 0.828 was calculated for the questionnaire. To test the hypothesis, the Pearson correlation coefficient was used. To ensure the correctness of initial theoretical model, we used regression analyzes and structural equation weight and finally, the results obtained with little change to the basic model of research, are improved and completed. At last obtain the perceived value has most direct effect on online car customers satisfaction.

Keywords: customer satisfaction, online satisfaction, online customer, car

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Authors: A. Al Drees, A. Alahmari, R. Almuwayshir

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The advanced information technology is becoming an important factor in the development of financial services industry, especially the banking industry. It has introduced new ways of delivering banking to the customer, such as Internet Banking. Banks began to look at electronic banking (e-banking) as a means to replace some of their traditional branch functions using the Internet as a new distribution channel. Some consumers have at least more than one account, and across banks, and access these accounts using e-banking services. To look at the current net worth position, customers have to login to each of their accounts and get the details and work on consolidation. This not only takes ample time but it is a repetitive activity at a specified frequency. To address this point, an account aggregation concept is added as a solution. E-banking account aggregation, as one of the e-banking types, appeared to build a stronger relationship with customers. Account Aggregation Service generally refers to a service that allows customers to manage their bank accounts maintained in different institutions through a common Internet banking operating a platform, with a high concern to security and privacy. This paper presents an overview of an e-banking account aggregation approach as a new service in the e-banking field.

Keywords: e-banking, account aggregation, security, enterprise development

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Authors: Priya Nangia, Sanchita Bansal

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As fashion cycles become more rapid, some segments of the fashion industry have adopted increasingly unsustainable production processes to keep up with demand and enhance profit margins. The growing threat to environmental and social wellbeing posed by unethical fast fashion practices and the need to integrate the targets of SDGs into this industry necessitates a shift in the fashion industry's unsustainable nature, which can only be accomplished in the long run if consumers support sustainable fashion by purchasing it. Fast fashion is defined as low-cost, trendy apparel that takes inspiration from the catwalk or celebrity culture and rapidly transforms it into garments at high-street stores to meet consumer demand. Given the importance of identity formation to many consumers, the desire to be “fashionable” often outweighs the desire to be ethical or sustainable. This paradox exemplifies the tension between the human drive to consume and the will to do so in moderation. Previous research suggests that there is an attitude-behavior gap when it comes to determining consumer purchasing behavior, but to the best of our knowledge, no study has analysed how to encourage customers to shift from fast to slow fashion. Against this backdrop, the aim of this study is twofold: first, to identify and examine the factors that impact consumers' decisions to engage in sustainable fashion, and second, the authors develop a comprehensive framework for conceptualizing and encouraging researchers and practitioners to foster sustainable consumer behavior. This study used a systematic approach to collect data and analyse literature. The approach included three key steps: review planning, review execution, and findings reporting. Authors identified the keywords “sustainable consumption” and “sustainable fashion” and retrieved studies from the Web of Science (WoS) (126 records) and Scopus database (449 records). To make the study more specific, the authors refined the subject area to management, business, and economics in the second step, retrieving 265 records. In the third step, the authors removed the duplicate records and manually reviewed the articles to examine their relevance to the research issue. The final 96 research articles were used to develop this study's systematic scheme. The findings indicate that societal norms, demographics, positive emotions, self-efficacy, and awareness all have an effect on customers' decisions to purchase sustainable apparel. The authors propose a framework, denoted by the acronym SHIFT, in which consumers are more likely to engage in sustainable behaviors when the message or context leverages the following factors: (s)social influence, (h)habit formation, (i)individual self, (f)feelings, emotions, and cognition, and (t)tangibility. Furthermore, the authors identify five broad challenges that encourage sustainable consumer behavior and use them to develop novel propositions. Finally, the authors discuss how the SHIFT framework can be used in practice to drive sustainable consumer behaviors. This research sought to define the boundaries of existing research while also providing new perspectives on future research, with the goal of being useful for the development and discovery of new fields of study, thereby expanding knowledge.

Keywords: consumer behavior, fast fashion, sustainable consumption, sustainable fashion, systematic literature review

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Authors: Yu Hung Chiang, Hei Chia Wang

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Nowadays, tourism has become a part of life. Before reserving hotels, customers need some information, which the most important source is online reviews, about hotels to help them make decisions. Due to the dramatic growing of online reviews, it is impossible for tourists to read all reviews manually. Therefore, designing an automatic review analysis system, which summarizes reviews, is necessary for them. The main purpose of the system is to understand the opinion of reviews, which may be positive or negative. In other words, the system would analyze whether the customers who visited the hotel like it or not. Using sentiment analysis methods will help the system achieve the purpose. In sentiment analysis methods, the targets of opinion (here they are called the feature) should be recognized to clarify the polarity of the opinion because polarity of the opinion may be ambiguous. Hence, the study proposes an unsupervised method using Part-Of-Speech pattern and multi-lexicons sentiment analysis to summarize all reviews. We expect this method can help customers search what they want information as well as make decisions efficiently.

Keywords: text mining, sentiment analysis, product feature extraction, multi-lexicons

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Authors: Pedram Behyar, Zahra Bayat

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The internet and web are changing ways of “far reaching scope and potential for transformation of the marketing functions”. The web is developing in a faster rate than any previous new communication medium. The website of destination has become a crucial branding channel, that is why all businesses are changing their way to communicate with their customers to encounter their needs and wants in better ways. Website provides numerous opportunities for businesses to strengthen their relationship with their customers. One of these opportunities is website component that enables internet users to make two-way communication with the businesses.

Keywords: marketing communication, brand image, usability, privacy and security, personalization and customization, responsiveness, customer online web experience

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Authors: Ali Muhammad

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The purpose of this study is to develop a theoretical framework which demonstrates the effect of four personal factors on employees rule following behavior in Kuwaiti business organizations. The model suggested in this study includes organizational citizenship behavior, affective organizational commitment, organizational trust, and procedural justice as possible predictors of rule following behavior. The study also attempts to compare the effects of the suggested factors on employees rule following behavior. The new model will, hopefully, extend previous research by adding new variables to the models used to explain employees rule following behavior. A discussion of issues related to rule-following behavior is presented, as well as recommendations for future research.

Keywords: employee adherence to rules, organizational justice, organizational commitment, organizational citizenship behavior

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Authors: S. R. Nikhashemi, Laily Haj Paim, Ali Khatibi

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Structural Equation Modeling (SEM) was used to test a hypothesized model explaining Malaysian hypermarket customers’ perceptions of brand trust (BT), customer perceived value (CPV) and perceived service quality (PSQ) on building their brand loyalty (CBL) and generating positive word-of-mouth communication (WOM). Self-administered questionnaires were used to collect data from 374 Malaysian hypermarket customers from Mydin, Tesco, Aeon Big and Giant in Kuala Lumpur, a metropolitan city of Malaysia. The data strongly supported the model exhibiting that BT, CPV and PSQ are prerequisite factors in building customer brand loyalty, while PSQ has the strongest effect on prediction of customer brand loyalty compared to other factors. Besides, the present study suggests the effect of the aforementioned factors via customer brand loyalty strongly contributes to generate positive word of mouth communication.

Keywords: brand trust, perceived value, Perceived Service Quality, Brand loyalty, positive word of mouth communication

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Authors: Guilherme Gorgulho, Carlos Roberto Camello Lima

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Due to the competitive market in which companies are currently engaged, the constant changes require companies to react quickly regarding the variability of demand and process. The changes are caused by customers, or by demand fluctuations or variations of products, or the need to serve customers within agreed delivery taking into account the continuous search for quality and competitive prices in products. These changes end up influencing directly or indirectly the activities of the Planning and Production Control (PPC), which does business in strategic, tactical and operational levels of production systems. One area of concern for organizations is in the short term (operational level), because this planning stage any error or divergence will cause waste and impact on the delivery of products on time to customers. Thus, this study aims to optimize the efficiency of production scheduling, using different sequencing strategies in an automotive company. Seeking to aim the proposed objective, we used the computer simulation in conjunction with lean manufacturing to build and validate the current model, and subsequently the creation of future scenarios.

Keywords: computational simulation, lean manufacturing, production scheduling, sequencing strategies

Procedia PDF Downloads 243

Authors: Sushma Ghogale

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With a surge in user-generated content or feedback or reviews on the internet, it has become possible and important to know consumers' opinions about products and services. This data is important for both potential customers and businesses providing the services. Data from social media is attracting significant attention and has become the most prominent channel of expressing an unregulated opinion. Prospective customers look for reviews from experienced customers before deciding to buy a product or service. Several websites provide a platform for users to post their feedback for the provider and potential customers. However, the biggest challenge in analyzing such data is in extracting latent features and providing term-level analysis of the data. This paper proposes an approach to use topic modeling to classify the reviews into topics and conduct sentiment analysis to mine the opinions. This approach can analyse and classify latent topics mentioned by reviewers on business sites or review sites, or social media using topic modeling to identify the importance of each topic. It is followed by sentiment analysis to assess the satisfaction level of each topic. This approach provides a classification of hotel reviews using multiple machine learning techniques and comparing different classifiers to mine the opinions of user reviews through sentiment analysis. This experiment concludes that Multinomial Naïve Bayes classifier produces higher accuracy than other classifiers.

Keywords: latent Dirichlet allocation, topic modeling, text classification, sentiment analysis

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Authors: Seyed Reza Agha Seyed Hosseini, Nicolas Hamelin

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Many marketing executives are looking for a comprehensive plan for delivering quality services and products that will create a distinct and unforgettable long-term experience for customers in dealing with their brand. Various brand management experts believe that a company looking to enhance its brand experience in the minds of customers should have a plan to increase customer satisfaction as well as customer loyalty. The purpose of this research was to investigate the role of brand experience in customer satisfaction and customer loyalty in Ayandeh Bank branches in Tehran. The study employed a quantitative methodology. For data gathering, a questionnaire was utilised to measure all the variables of the research. The statistical population of the study consisted of all the customers of Ayandeh Bank branches in Tehran, and the study data was gathered from 400 respondents. The findings indicate that brand experience has a direct and meaningful impact on customer satisfaction and customer loyalty, and, furthermore, that customer satisfaction has a direct and significant effect on customer loyalty in the branches of Ayandeh Bank in Tehran.

Keywords: brand experience, customer satisfaction, customer loyalty, bank

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Authors: Rhay-Hung Weng, Ching-Yuan Huang, Wan-Ping Chen

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Recently, many hospitals have put much emphasis upon the development of nurse innovation. The present study aimed to clarify how nurse innovation is related to medical service quality and medical service experience. This study adopted questionnaire-survey method with nurses and customers of the inpatient wards from three Taiwanese hospitals as the research subjects. After pairing, there were 294 valid questionnaires. Hierarchical regression analysis was utilized to test the possible impact of nurse innovation on medical service quality and experience. In terms of the dimensions of nurse innovation, “innovation behavior” ranked the highest (3.24), followed by knowledge creation and innovation diffusion; in terms of the degree of the medical service quality, 'reliability' ranked the highest (4.35). As for the degree of the medical service experience, 'feel experience' ranked the highest (4.44). All dimensions of nurse innovation have no significant effects on medical service quality and medical service experience. Of these three dimensions of nurse innovation, the level of innovation behavior was perceived by the nurses as the highest. The study found that nurse innovation has no significant effects on medical service quality and medical service experience. Managers shall provide sufficient resources and budget for fostering innovation development and encourage their nurses to develop nursing innovation for patents. The education and training courses on “patient-centered ” shall be enhanced among hospital nurses. Health care managers shall also explore the difficulties about innovation diffusion and find the solutions for nurses.

Keywords: innovation, employee innovative behavior, service quality, service experience

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Authors: Jiraporn Weenuttranon

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The objectives of the consumer behavior of bakery products in Bangkok are to study consumer behavior of the bakery product, to study the essential factors that could possibly affect the consumer behavior and to study recommendations for the development of the bakery products. This research is a survey research. Populations are buyer’s bakery products in Bangkok. The probability sample size is 400. The research uses a questionnaire for self-learning by using information technology. The researcher created a reliability value at 0.71 levels of significance. The data analysis will be done by using the percentage, mean, and standard deviation and testing the hypotheses by using chi-square.

Keywords: consumer, behavior, bakery, standard deviation

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Authors: Epaminondas G. Kyriakidis, Theodosis D. Dimitrakos, Constantinos C. Karamatsoukis

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The vehicle routing problem (VRP) is a well-known problem in Operations Research and has been widely studied during the last fifty-five years. The context of the VRP is that of delivering products located at a central depot to customers who are scattered in a geographical area and have placed orders for these products. A vehicle or a fleet of vehicles start their routes from the depot and visit the customers in order to satisfy their demands. Special attention has been given to the capacitated VRP in which the vehicles have limited carrying capacity of the goods that must be delivered. In the present work, we present a specific capacitated stochastic vehicle routing problem which has realistic applications to distributions of materials to shops or to healthcare facilities or to military units. A vehicle starts its route from a depot loaded with items of two similar but not identical products. We name these products, product 1 and product 2. The vehicle must deliver the products to N customers according to a predefined sequence. This means that first customer 1 must be serviced, then customer 2 must be serviced, then customer 3 must be serviced and so on. The vehicle has a finite capacity and after servicing all customers it returns to the depot. It is assumed that each customer prefers either product 1 or product 2 with known probabilities. The actual preference of each customer becomes known when the vehicle visits the customer. It is also assumed that the quantity that each customer demands is a random variable with known distribution. The actual demand is revealed upon the vehicle’s arrival at customer’s site. The demand of each customer cannot exceed the vehicle capacity and the vehicle is allowed during its route to return to the depot to restock with quantities of both products. The travel costs between consecutive customers and the travel costs between the customers and the depot are known. If there is shortage for the desired product, it is permitted to deliver the other product at a reduced price. The objective is to find the optimal routing strategy, i.e. the routing strategy that minimizes the expected total cost among all possible strategies. It is possible to find the optimal routing strategy using a suitable stochastic dynamic programming algorithm. It is also possible to prove that the optimal routing strategy has a specific threshold-type structure, i.e. it is characterized by critical numbers. This structural result enables us to construct an efficient special-purpose dynamic programming algorithm that operates only over those routing strategies having this structure. The findings of the present study lead us to the conclusion that the dynamic programming method may be a very useful tool for the solution of specific vehicle routing problems. A problem for future research could be the study of a similar stochastic vehicle routing problem in which the vehicle instead of delivering, it collects products from ordered customers.

Keywords: collection of similar products, dynamic programming, stochastic demands, stochastic preferences, vehicle routing problem

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Authors: Wang Lin, Li Zhiqiang

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The purpose of this paper is to analyze the cooperative learning behavior pattern based on the data of students' movement. The study firstly reviewed the cooperative learning theory and its research status, and briefly introduced the k-means clustering algorithm. Then, it used clustering algorithm and mathematical statistics theory to analyze the activity rhythm of individual student and groups in different functional areas, according to the movement data provided by 10 first-year graduate students. It also focused on the analysis of students' behavior in the learning area and explored the law of cooperative learning behavior. The research result showed that the cooperative learning behavior analysis method based on movement data proposed in this paper is feasible. From the results of data analysis, the characteristics of behavior of students and their cooperative learning behavior patterns could be found.

Keywords: behavior pattern, cooperative learning, data analyze, k-means clustering algorithm

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Authors: A. Hakimiyan, H. Namazi

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Human behavior is defined as a range of behaviors exhibited by humans who are influenced by different internal or external sources. Human behavior is the subject of much research in different areas of psychology and neuroscience. Despite some advances in studies related to forecasting of human behavior, there are not many researches which consider the effect of the time delay between the presence of stimulus and the related human response. Analysis of EEG signal as a fractal time series is one of the major tools for studying the human behavior. In the other words, the human brain activity is reflected in his EEG signal. Artificial Neural Network has been proved useful in forecasting of different systems’ behavior especially in engineering areas. In this research, a time delay neural network is trained and tested in order to forecast the human EEG signal and subsequently human behavior. This neural network, by introducing a time delay, takes care of the lagging time between the occurrence of the stimulus and the rise of the subsequent action potential. The results of this study are useful not only for the fundamental understanding of human behavior forecasting, but shall be very useful in different areas of brain research such as seizure prediction.

Keywords: human behavior, EEG signal, time delay neural network, prediction, lagging time

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Authors: Rabih Nehme, Abdullah Al Mutawa

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The general goal behind this research is to gain a better understanding of factors leading to dysfunctional behavior of auditors. Recent accounting scandals -Enron, Waste Management Inc., WorldCom, Xerox Corporation, etc. -provided an ample proof of how the role of auditors has become the basis of controversial debates in many circles and instances in our modern time. The majority of lawsuits and accounting scandals seem to have a central topic in focus, namely the question ''Where were the auditors? The survey we offer up for research is made up of 34 questions that are designed to analyse the perception of auditors and the cause of dysfunctional behavior. The object of this research is comprised of auditors positioned and employed at the Big Four audit firms in Kuwait. Dysfunctional behavior (DB) is measured against two signal proxies of dysfunctional behavior; premature sign-off and under reporting of chargeable time. DB is analysed against time budget pressure and time deadline pressure. The research results' suggest that the general belief among auditors is that the profession of accountancy predetermines their tendency to commit certain patterns of dysfunctional behavior. Having our investigation conducted at the Big Four audit firms, we have come to the conclusion that there is a general difference in behavior patterns among perceptions of dysfunctional behavior and normal skeptic professional behavior.

Keywords: big four, dysfunctional behavior, time budget, time deadline

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Authors: Khaled Moh. Alhamad

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This paper describes a tabu search heuristic for a ship routing and scheduling problem (SRSP). The method was developed to address the problem of loading cargos for many customers using heterogeneous vessels. Constraints relate to delivery time windows imposed by customers, the time horizon by which all deliveries must be made and vessel capacities. The results of a computational investigation are presented. Solution quality and execution time are explored with respect to problem size and parameters controlling the tabu search such as tenure and neighbourhood size.

Keywords: heuristic, scheduling, tabu search, transportation

Procedia PDF Downloads 478

Authors: Abd Latif Abdul Rahman, Zuraidah Arif, Muhammad Faizal Iylia, Mohd Ghazali, Asmadi Mohammed Ghazali

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Mobile information is a significant access point for human information activities. Theories and models of human information behavior have developed over several decades but have not yet considered the role of the user’s computing device in digital information interactions. This paper reviews the literature that leads to developing a conceptual framework of a study on the managers mobile information behavior. Based on the literature review, dimensions of mobile information behavior are identified, namely, dimension information needs, dimension information access, information retrieval and dimension of information use. The study is significant to understand the nature of librarians’ behavior in searching, retrieving and using information via the mobile device. Secondly, the study would provide suggestions about various kinds of mobile applications which organization can provide for their staff to improve their services.

Keywords: mobile information behavior, information behavior, mobile information, mobile devices

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Authors: Seher Arslankaya, Bahar Uludağ

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Meeting the needs and demands of customers and pleasing the customers are important requirements for companies in food sectors where the growth of competition is significantly unpredictable. Customer satisfaction is also one of the key concepts which is mainly driven by wide range of customer preference and expectation upon products and services introduced and delivered to them. In order to meet the customer demands, the companies that engage in food sectors are expected to have a well-managed set of Total Quality Management (TQM), which sets out to improve quality of products and services; to reduce costs and to increase customer satisfaction by restructuring traditional management practices. It aims to increase customer satisfaction by meeting (their) customer expectations and requirements. The achievement would be determined with the help of customer satisfaction surveys, which is done to obtain immediate feedback and to provide quick responses. In addition, the surveys would also assist the making of strategic planning which helps to anticipate customer future needs and expectations. Meanwhile, periodic measurement of customer satisfaction would be a must because with the better understanding of customers perceptions from the surveys (done by questioners), the companies would have a clear idea to identify their own strengths and weaknesses that help the companies keep their loyal customers; to stand in comparison toward their competitors and map out their future progress and improvement. In this study, we propose a survey based on customer satisfaction measurement method and its statistical analysis for sales and logistic activities of food firms. Customer satisfaction would be discussed in details. Furthermore, after analysing the data derived from the questionnaire that applied to customers by using the SPSS software, various results obtained from the application would be presented. By also applying ANOVA test, the study would analysis the existence of meaningful differences between customer demographic proportion and their perceptions. The purpose of this study is also to find out requirements which help to remove the effects that decrease customer satisfaction and produce loyal customers in food industry. For this purpose, the customer complaints are collected. Additionally, comments and suggestions are done according to the obtained results of surveys, which would be useful for the making-process of strategic planning in food industry.

Keywords: customer satisfaction measurement and analysis, food industry, SPSS, TQM

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Authors: Phatthanan Chaiyabut

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The purposes of this research were to identify the perception of customers towards Krung Thai Bank’s image and to understand the customer attitude towards Krung Thai Bank’s image in Bangkok, Thailand. This research utilized quantitative approach and used questionnaire as data collection tool. A sample size of 420 respondents was selected by simple random sampling. The findings revealed that the majority of respondents received information, news, and feeds concerning the bank through televisions the most. This information channel had significantly influenced on the customers and their decisions to utilize the bank’s products and services. From the information concerning the attitudes towards overall image of the bank, it was found that the majority respondents rated the bank’s image at the good level. The top three average attitudes included the bank’s images in supports government's monetary policies, being renowned and stable, and contributing in economical amendments and developments, with the mean average of 4.01, 3.96 and 3.81 respectively. The attitudes toward the images included a business leader in banking, marketing, and competitions. Offering prompt services, and provided appropriate servicing time were rated moderate with the attitudes of 3.36 and 3.30 respectively.

Keywords: attitude, image, Krung Thai Bank, perception

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Authors: R. Remya

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We consider an M/M/1 multiple variant vacation queueing system and working vacation with waiting server. Here, comparing considering three models. First model, working vacation is taken after the server has exhaustively served all the customers in the system and waits random amount of time. After completing a working vacation, the server will wait for a random period of time before going on vacation. Then it goes to finite number of vacations same way. After end of J th vacation server waits in busy or served immediately. Second model, working vacation is taken after the server has exhaustively served all the customers in the system and waits random amount of time. Third model, working vacation is taken after the server has exhaustively served all the customers in the system and waits random amount of time. It is expected that service times and vacation lengths are exponentially distributed . We provide a steady-state solution and cost comparison for the stated models.

Keywords: vacation, working vacation, waiting server, steady state analysis, cost analysis

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Authors: Fereshteh Nazeri Bahadori

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In today's competitive environment, any company that aims to operate in a market, whether industrial or consumer markets, must know that it cannot address all the tastes and demands of customers at once and serve them all. The study of consumer memory is considered an important subject in marketing research, and many companies have conducted studies on this subject and the factors affecting it due to its importance. Therefore, the current study tries to investigate the relationship between consumers' attention, literacy, and memory. Memory has a very close relationship with learning. Memory is the collection of all the information that we have understood and stored. One of the important subjects in consumer behavior is information processing by the consumer. One of the important factors in information processing is the mental involvement of the consumer, which has attracted a lot of attention in the past two decades. Since consumers are the turning point of all marketing activities, successful marketing begins with understanding why and how consumers behave. Therefore, in the current study, the role of executive attention and literacy on consumers' memory has been investigated. The results showed that executive attention and literacy would play a significant role in the long-term and short-term memory of consumers.

Keywords: literacy, consumer memory, executive attention, psychology of consumer behavior

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Authors: Fikri, Rozmi Ismail, Fatimah Wati Halim, Sarah Waheeda

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The aim of this research is to investigate the influence of personality and driver behavior on road accident among bus driver who have the high risk behavior on road accident in Riau Province. The hypotheses proposed this research is there are has a significant influences of Treat of Personality and Driver Behavior among bus driver in Riau Province Indonesia. Subject participated in this research are 100 bus driver in Riau Province. This study using the purposive random sampling technique and quantitative design. The data is collected using the Big Five Personality questionnaires, Driver Behavior questionnaires and Road Accident Inventory. Research found that there are significant influence of personality and driver behavior on road accident among bus driver in Riau Province Indonesia.

Keywords: personality, driver behavior, driver stress, road accident

Procedia PDF Downloads 453