Search results for: customer segments

Authors: Omar Ramzi Jasim, Jalal Sultan Ashour

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Production Planning or Master Production Schedule (MPS) is a key interface between marketing and manufacturing, since it links customer service directly to efficient use of production resources. Mismanagement of the MPS is considered as one of fundamental problems in operation and it can potentially lead to poor customer satisfaction. In this paper, a hybrid evolutionary algorithm (ICA-GA) is presented, which integrates the merits of both imperialist competitive algorithm (ICA) and genetic algorithm (GA) for solving multi-objective MPS problems. In the presented algorithm, the colonies in each empire has be represented a small population and communicate with each other using genetic operators. By testing on 5 production scenarios, the numerical results of ICA-GA algorithm show the efficiency and capabilities of the hybrid algorithm in finding the optimum solutions. The ICA-GA solutions yield the lower inventory level and keep customer satisfaction high and the required overtime is also lower, compared with results of GA and SA in all production scenarios.

Keywords: master production scheduling, genetic algorithm, imperialist competitive algorithm, hybrid algorithm

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Authors: Lou-Hon Sun, Yu-Ming Chiu, Chen-Wei Tao, Chia-Yun Tsai

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It is common practice for many companies to ask employees to provide heart-touching service for customers and to emphasize the attitude of 'customer first'. However, services may not necessarily gain praise, and may actually be considered excessive, if customers do not appreciate such behaviors. In reality, many restaurant businesses try to provide as much service as possible without taking into account whether over-provision may lead to negative customer reception. A survey of 894 people in Britain revealed that 49 percent of respondents consider over-attentive waiters the most annoying aspect of dining out. It can be seen that merely aiming to exceed customers’ expectations without actually addressing their needs, only further distances and dissociates the standard of services from the goals of customer satisfaction itself. Over-service is defined, as 'service provided that exceeds customer expectations, or simply that customers deemed redundant, resulting in negative perception'. It was found that customers’ reactions and complaints concerning over-service are not as intense as those against service failures caused by the inability to meet expectations; consequently, it is more difficult for managers to become aware of the existence of over-service. Thus the ability to manage over-service behaviors is a significant topic for consideration. The Kano model classifies customer preferences into five categories: attractive quality attribute, one-dimensional quality attribute, must-be quality attribute, indifferent quality attribute and reverse quality attributes. The model is still very popular for researchers to explore the quality aspects and customer satisfaction. Nevertheless, several studies indicated that Kano’s model could not fully capture the nature of service quality. The concept of over-service can be used to restructure the model and provide a better understanding of the service quality construct. In this research, the structure of Kano's two-dimensional questionnaire will be used to classify the factors into different dimensions. The same questions will be used in the second questionnaire for identifying the over-service experienced of the respondents. The finding of these two questionnaires will be used to analyze the relevance between service quality classification and over-service behaviors. The subjects of this research are customers of fine dining chain restaurants. Three hundred questionnaires will be issued based on the stratified random sampling method. Items for measurement will be derived from DINESERV scale. The tangible dimension of the questionnaire will be eliminated due to this research is focused on the employee behaviors. Quality attributes of the Kano model are often regarded as an instrument for improving customer satisfaction. The concept of over-service can be used to restructure the model and provide a better understanding of service quality construct. The extension of the Kano model will not only develop a better understanding of customer needs and expectations but also enhance the management of service quality.

Keywords: consumer satisfaction, DINESERV, kano model, over-service

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Authors: Luis N. Pereira, Marco P. Carrasco

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Dynamic pricing is a revenue management strategy in which hotel suppliers define, over time, flexible and different prices for their services for different potential customers, considering the profile of e-consumers and the demand and market supply. This means that the fundamentals of dynamic pricing are based on economic theory (price elasticity of demand) and market segmentation. This study aims to define a dynamic pricing strategy and a contextualized offer to the e-consumers profile in order to improve the number of reservations of an online distribution channel. Segmentation methods (hierarchical and non-hierarchical) were used to identify and validate an optimal number of market segments. A profile of the market segments was studied, considering the characteristics of the e-consumers and the probability of reservation a room. In addition, the price elasticity of demand was estimated for each segment using econometric models. Finally, predictive models were used to define rules for classifying new e-consumers into pre-defined segments. The empirical study illustrates how it is possible to improve the intelligence of an online distribution channel system through an optimal dynamic pricing strategy and a contextualized offer to the profile of each new e-consumer. A database of 11 million e-consumers of an online distribution channel was used in this study. The results suggest that an appropriate policy of market segmentation in using of online reservation systems is benefit for the service suppliers because it brings high probability of reservation and generates more profit than fixed pricing.

Keywords: dynamic pricing, e-consumers segmentation, online reservation systems, predictive analytics

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Authors: Harpreet Singh

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Finding relevant information on the World Wide Web is becoming highly challenging day by day. Web usage mining is used for the extraction of relevant and useful knowledge, such as user behaviour patterns, from web access log records. Web access log records all the requests for individual files that the users have requested from the website. Web usage mining is important for Customer Relationship Management (CRM), as it can ensure customer satisfaction as far as the interaction between the customer and the organization is concerned. Web usage mining is helpful in improving website structure or design as per the user’s requirement by analyzing the access log file of a website through a log analyzer tool. The focus of this paper is to enhance the accessibility and usability of a guitar selling web site by analyzing their access log through Deep Log Analyzer tool. The results show that the maximum number of users is from the United States and that they use Opera 9.8 web browser and the Windows XP operating system.

Keywords: web usage mining, web mining, log file, data mining, deep log analyzer

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Authors: Sabri Serkan Güllüoğlu

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Analysis can be defined as the process of gathering, recording and researching data related to products and services, in order to learn something. But for marketers, analyses are not only used for learning but also an essential and critical part of the business, because this allows companies to offer products or services which are focused and well targeted. Market analysis also identify market trends, demographics, customer’s buying habits and important information on the competition. Data mining is used instead of traditional research, because it extracts predictive information about customer and sales from large databases. In contrast to traditional research, data mining relies on information that is already available. Simply the goal is to improve the efficiency of supermarkets. In this study, the purpose is to find dependency on products. For instance, which items are bought together, using association rules in data mining. Moreover, this information will be used for improving the profitability of customers such as increasing shopping time and sales of fewer sold items.

Keywords: data mining, association rule mining, market basket analysis, purchasing

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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: Priscila A. Bernardes, Marcos E. Buzanskas, Luciana C. A. Regitano, Ricardo V. Ventura, Danisio P. Munari

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The best linear unbiased predictor (BLUP) is a method commonly used in genetic evaluations of breeding programs. However, this approach can lead to higher inbreeding coefficients in the population due to the intensive use of few bulls with higher genetic potential, usually presenting some degree of relatedness. High levels of inbreeding are associated to low genetic viability, fertility, and performance for some economically important traits and therefore, should be constantly monitored. Unreliable pedigree data can also lead to misleading results. Genomic information (i.e., single nucleotide polymorphism – SNP) is a useful tool to estimate the inbreeding coefficient. Runs of homozygosity have been used to evaluate homozygous segments inherited due to direct or collateral inbreeding and allows inferring population selection history. This study aimed to evaluate runs of homozygosity (ROH) and inbreeding in a population of Nelore beef cattle. A total of 814 animals were genotyped with the Illumina BovineHD BeadChip and the quality control was carried out excluding SNPs located in non-autosomal regions, with unknown position, with a p-value in the Hardy-Weinberg equilibrium lower than 10⁻⁵, call rate lower than 0.98 and samples with the call rate lower than 0.90. After the quality control, 809 animals and 509,107 SNPs remained for analyses. For the ROH analysis, PLINK software was used considering segments with at least 50 SNPs with a minimum length of 1Mb in each animal. The inbreeding coefficient was calculated using the ratio between the sum of all ROH sizes and the size of the whole genome (2,548,724kb). A total of 25.711 ROH were observed, presenting mean, median, minimum, and maximum length of 3.34Mb, 2Mb, 1Mb, and 80.8Mb, respectively. The number of SNPs present in ROH segments varied from 50 to 14.954. The longest ROH length was observed in one animal, which presented a length of 634Mb (24.88% of the genome). Four bulls were among the 10 animals with the longest extension of ROH, presenting 11% of ROH with length higher than 10Mb. Segments longer than 10Mb indicate recent inbreeding. Therefore, the results indicate an intensive use of few sires in the studied data. The distribution of ROH along the chromosomes showed that chromosomes 5 and 6 presented a large number of segments when compared to other chromosomes. The mean, median, minimum, and maximum inbreeding coefficients were 5.84%, 5.40%, 0.00%, and 24.88%, respectively. Although the mean inbreeding was considered low, the ROH indicates a recent and intensive use of few sires, which should be avoided for the genetic progress of breed.

Keywords: autozygosity, Bos taurus indicus, genomic information, single nucleotide polymorphism

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Authors: Ebrahim Gharleghi

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This paper aims to examine how customer knowledge management (CKM) can be implemented in Iranian Banks in practice, with the focus on the human resource (people, technology and processes) as important factors of CKM. A conceptual model of an analytical CKM strategy for CKM in this Iranian Banks is developed from the findings and literature review. This article has been based on interviews and distributing the questionnaire. Data were collected from 260 managers from bank managers. The paper finds that hypotheses were tested using student’s t-test (one-sample t-test), Pearson correlation analysis and regression analysis. Test of hypotheses revealed that human, technology and processes factors positively and significantly influenced the implementation of CKM practices. These findings tend to corroborate our conceptual model. Human factor of CKM was found to be more significantly affecting appropriate CKM implementation than others CKM factors, indicating that this factor is more important than the others aspects of CKM. On the other hand, this factor is appropriate in Iranian Banks. Process is in second part and technology is in final part. This indicates that technology infrastructures are so weak in Iranian Banks for CKM implementation. In this paper there is little or no empirical evidence investigating the amount of the execution of the CKM in Iranian Banks. This paper rectifies this imbalance by clarifying the significance human, technology and processes factors in CKM implementation.

Keywords: knowledge management, customer relationship management, customer knowledge management, integration, people, technology, process

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Authors: Habte Tadesse Likassa, Bacha Edosa

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Customer’s satisfaction was very important thing that is required for the existence of banks to be more productive and success in any organization and business area. The main goal of the study is assessing and identifying factors that influence customer’s satisfaction in West Shoa Zone of Commercial Bank of Ethiopia (Holeta, Ginchi, Ambo, Gedo and Bako). Stratified random sampling procedure was used in the study and by using simple random sampling (lottery method) 520 customers were drawn from the target population. By using Probability Proportional Size Techniques sample size for each branch of banks were allocated. Both descriptive and inferential statistics methods were used in the study. A binary logistic regression model was fitted to see the significance of factors affecting customer’s satisfaction in this study. SPSS statistical package was used for data analysis. The result of the study reveals that the overall level of customer’s satisfaction in the study area is low (38.85%) as compared those who were not satisfied (61.15%). The result of study showed that all most all factors included in the study were significantly associated with customer’s satisfaction. Therefore, it can be concluded that based on the comparison of branches on their customers satisfaction by using odd ratio customers who were using Ambo and Bako are less satisfied as compared to customers who were in Holeta branch. Additionally, customers who were in Ginchi and Gedo were more satisfied than that of customers who were in Holeta. Since the level of customers satisfaction was low in the study area, it is more advisable and recommended for concerned body works cooperatively more in maximizing satisfaction of their customers.

Keywords: customers, satisfaction, binary logistic, complain handling process, waiting time

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Authors: Jeongwoo Lee

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Children are the most vulnerable travelers and they are at risk for pedestrian injury. Creating a safe route to school is important because walking to school is one of the main opportunities for promotion of needed physical exercise among children. This study examined how the built environmental attributes near an elementary school influence traffic accidents among school-aged children. The study used two complementary data sources including the locations of police-reported pedestrian crashes and the built environmental characteristics of school areas. The environmental attributes of road segments were collected through GIS measurements of local data and actual site audits using the inventory developed for measuring pedestrian-crash risk scores. The inventory data collected at 840 road segments near 32 elementary schools in the city of Ulsan. We observed all segments in a 300-meter-radius area from the entrance of an elementary school. Segments are street block faces. The inventory included 50 items, organized into four domains: accessibility (17items), pleasurability (11items), perceived safety from traffic (9items), and traffic and land-use measures (13items). Elementary schools were categorized into two groups based on the distribution of the pedestrian-crash hazard index scores. A high pedestrian-crash zone was defined as an school area within the eighth, ninth, and tenth deciles, while no pedestrian-crash zone was defined as a school zone with no pedestrian-crash accident among school-aged children between 2013 and 2016. No- and high pedestrian-crash zones were compared to determine whether different settings of the built environment near the school lead to a different rate of pedestrian-crash incidents. The results showed that a crash risk can be influenced by several environmental factors such as a shape of school-route, number of intersections, visibility and land-use in a street, and a type of sidewalk. The findings inform policy for creating safe routes to school to reduce the pedestrian-crash risk among children by focusing on school zones.

Keywords: active school travel, school zone, pedestrian crash, safety route to school

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Authors: Leena Wanganoo

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In this digital age with the mushrooming of online companies across the globe has led to an unprecedented new business model. The frequency of online purchasing varies across the globe, but trend shows a steep upward movement. From Generation X to the Millennial the consumer not only wants to order the product with the click of mouse but also very demanding service quality during pre to post-transaction stage. The existing research examines the impact of website quality on the on behavioral intentions in e-services customers and has not adequately recognized the quality of e-commerce logistics perceived by the customer.In order to address this gap, this study examines the relationship among the logistics service quality, satisfaction, and loyalty. Drawing upon a sample of 350 millennial customers from various regions of UAE will work within the framework of structural equation modeling (SEM). Finally, the study would use Importance-Performance analysis (IPA) to discuss the relations of the level of customers’ expected logistics service quality and level of customers’ perceived logistics serviced quality.

Keywords: logistics service quality, customer satisfaction, loyalty, electronic commerce

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Authors: Oshin Anand, Atanu Rakshit

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The vast increment in the e-commerce ventures makes this area a prominent research stream. Besides several quantified parameters, the textual content of reviews is a storehouse of many information that can educate companies and help them earn profit. This study is an attempt in this direction. The article attempts to categorize data based on a computed metric that quantifies the influencing capacity of reviews rendering two categories of high and low influential reviews. Further, each of these document is studied to conclude several product feature categories. Each of these categories along with the computed metric is converted to linguistic identifiers and are used in an association mining model. The article makes a novel attempt to combine feature attraction with quantified metric to categorize review text and finally provide frequent patterns that depict customer preferences. Frequent mentions in a highly influential score depict customer likes or preferred features in the product whereas prominent pattern in low influencing reviews highlights what is not important for customers. This is achieved using a hybrid approach of text mining for feature and term extraction, sentiment analysis, multicriteria decision-making technique and association mining model.

Keywords: association mining, customer preference, frequent pattern, online reviews, text mining

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Authors: Maziyar Nouraee

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Electronic markets in recent decades contribute remarkably in business transactions. Many organizations consider traditional ways of trade non-economical and therefore they do trade only through electronic markets. There are different categorizations of electronic markets functions. In one classification, functions of electronic markets are categorized into classes as information, transactions, and value added. In the present paper, effects of the three classes on the two major elements of the supply chain management are measured. The two elements are decrease in the product unit cost and reduction in response time to the customer. The results of the current research show that among nine minor elements related to the three classes of electronic markets functions, six factors and three factors influence on reduction of the product unit cost and reduction of response time to the customer, respectively.

Keywords: electronic commerce, electronic market, B2B trade, supply chain management

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Authors: Mohammad Zavid Parvez, Manoranjan Paul

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Epilepsy is a common neurological disorders characterized by sudden recurrent seizures. Electroencephalogram (EEG) is widely used to diagnose possible epileptic seizure. Many research works have been devoted to predict epileptic seizure by analyzing EEG signal. Seizure prediction by analyzing EEG signals are challenging task due to variations of brain signals of different patients. In this paper, we propose a new approach for feature extraction based on phase correlation in EEG signals. In phase correlation, we calculate relative change between two consecutive segments of an EEG signal and then combine the changes with neighboring signals to extract features. These features are then used to classify preictal/ictal and interictal EEG signals for seizure prediction. Experiment results show that the proposed method carries good prediction rate with greater consistence for the benchmark data set in different brain locations compared to the existing state-of-the-art methods.

Keywords: EEG, epilepsy, phase correlation, seizure

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Authors: Samil Ozcan

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Airlines companies target different customer segments in consideration of pricing, service quality, flight network, etc. and their brand positioning accords with the marketization strategies developed in the same direction. The object of this study, Turkish Airlines, has many peculiarities regarding its brand positioning as compared to its rivals in the sector. In the first place, it appeals to a global customer group because of its Star Alliance membership and its broad flight network with 315 destination points. The second group in its customer segmentation includes domestic customers. For this group, the company follows a marketing strategy that plays to local culture and accentuates the image of Turkishness as an emotional allurement. The advertisements and publicity projects designed in this regard put little emphasis on the service quality the company offers to its clients; it addresses the emotions of the consumers rather than individual benefits and relies on the historical memory of the nation and shared cultural values. This study examines the publicity work which aims at the second segment customer group focusing on Turkish Airlines’ 85th Anniversary Commercial through a symbolic meaning analysis approach. The commercial presents six stories with undertones of nationalism in its theme. Nationalism is not just the product of collective interests based on reason but a result of patriotism in the sense of loyalty to state and nation and love of ethnic belonging. While nationalism refers to concrete notions such as blood tie, common ancestor, shared history, it is not the actuality of these notions that it draws its real strength but the emotions invested in them. The myths of origin, the idea of common homeland, boundary definitions, and symbolic acculturation have instrumental importance in the development of these commonalities. The commercial offers concrete examples for an analysis of Connor’s definition of nationalism based on emotions. Turning points in the history of the Turkish Republic and the historical mission Turkish Airlines undertook in these moments are narrated in six stories in the commercial with a highly emotional theme. These emotions, in general, depend on collective memory generated by national consciousness. Collective memory is not simply remembering the past. It is constructed through the reconstruction and reinterpretation of the past in the present moment. This study inquires the motivations behind the nationalist emotions generated within the collective memory by engaging with the commercial released for the 85th anniversary of Turkish Airlines as the object of analysis. Symbols and myths can be read as key concepts that reveal the relation between 'identity and memory'. Because myths and symbols do not merely reflect on collective memory, they reconstruct it as well. In this sense, the theme of the commercial defines the image of Turkishness with virtues such as self-sacrifice, helpfulness, humanity, and courage through a process of meaning creation based on symbolic mythologizations like flag and homeland. These virtues go beyond describing the image of Turkishness and become an instrument that defines and gives meaning to Turkish identity.

Keywords: collective memory, emotions, identity, nationalism

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Authors: Idris Lawal

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Electronic payment system is simply a payment or monetary transaction made over the internet or a network of computers. This study was carried out in order to assess how electronic payment system has impacted on banks service delivery, to examine the efficiency of electronic payment system in Nigeria and to determine the level of customer's satisfaction as a direct result of the deployment of electronic payment systems. It is an empirical study conducted using structured questionnaire distributed to officials and customers of Access Bank plc. Chi-square(x2) was adopted for the purpose of data analysis. The result of the study showed that the development of electronic payment system offer great benefit to bank customers including improved services, reduced turn-around time, ease of banking transaction, significant cost saving etc. The study recommends that customer protection laws should be properly put in place to safeguard the interest of end users of e-payment instruments.

Keywords: bank, electronic payment systems, service delivery, customer's satisfaction

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Authors: Dwipa Rizki Utama, Hanief Ibrahim

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The development of industry retail in Indonesia is very fast, various strategy was undertaken to boost the customer satisfaction and the productivity purchases to boost the profit, one of which is implementing strategies layout. The purpose of this study is to determine the layout of Qita supermarket, a retail industry in Indonesia, in order to improve customer satisfaction and to maximize the rate of products’ sale as a whole, so as the infrequently purchased products will be purchased. This research uses a literature study method, and one of the data mining methods is association rule which applied in market basket analysis. Data were tested amounted 100 from 160 after pre-processing data, so then the distribution department and 26 departments corresponding to the data previous layout will be obtained. From those data, by the association rule method, customer behavior when purchasing items simultaneously can be studied, so then the layout of the supermarket based on customer behavior can be determined. Using the rapid miner software by the minimal support 25% and minimal confidence 30% showed that the 14th department purchased at the same time with department 10, 21st department purchased at the same time with department 13, 15th department purchased at the same time with department 12, 14th department purchased at the same time with department 12, and 10th department purchased at the same time with department 14. From those results, a better supermarket layout can be arranged than the previous layout.

Keywords: industry retail, strategy, association rule, supermarket

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Authors: Edward Hwang

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The efficiency of public policies depends on customer's satisfaction, and the change directions of public policies hinge on customer's assessment; i.e., the performance of public policies in governments is decided by the citizen's administrative satisfaction! The governments in all levels must heave their efficiency and effectiveness of public services to meet the people's substantially multiple needs in order to make citizens trust the governmental operation styles. To pursue the societal equality and justice, governments should treat people equally and provide more services for the disadvantages. The recent Dapu protest event involves Miaoli county Magistrate Liu cheng-hung who arbitrarily demolished houses and destroyed farmlands, and it shifts his popularity into disaffection. Liu case tells us that the political events are lethal to politicians; it cut almost 20% satisfaction degree for Magistrate Liu and hurt KMT support levels nationally. In terms of administrative satisfaction levels, political factors do matter, especially for the derogated events.

Keywords: local politics, administrative satisfaction, Taiwan, customer satisfaction

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Authors: C. A. Akaash Emmanuel Raj, V. R. Sanal Kumar

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In this paper using smart materials we have proposed a specially manufactured variable volume spin tub for loading clothes for negating the vibration to a certain extent for getting better operating performance. Additionally, we have recommended a variable spinning speed rotor for handling varieties of garments for an efficient washing, aiming for increasing the life span of both the garments and the machine. As a part of the conflicting dynamic constraints and demands of the customer friendly design optimization of a lucrative and cosmetic washing machine we have proposed a drier and a desalination system capable to supply desirable heat and a pleasing fragrance to the garments. We thus concluded that while incorporating variable volume and variable spinning speed tub integrated with a drier and desalination system, the washing machine could meet the varieties of domestic requirements of the customers cost-effectively.

Keywords: customer friendly washing machine, drier design, quick cloth cleaning, variable tub volume washing machine, variable spinning speed washing machine

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Authors: Kanamon Suwantada

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The purpose of this research is to understand customer’s expectations towards homestays and to establish the precise strategies to increase numbers of tourists for homestay business in Amphawa district, Samutsongkram, Thailand. The researcher aims to ensure that each host provides experiences to travelers who are looking for and determining new targets for homestay business in Amphawa as well as creating sustainable homestay using marketing strategies to increase customers. The methods allow interview and questionnaire to gain both overview data from the tourists and qualitative data from the homestay owner’s perspective to create a GAP analysis. The data was collected from 200 tourists, during 15th May - 30th July, 2011 from homestay in Amphawa Community. The questionnaires were divided into three sections: the demographic profile, customer information and influencing on purchasing position, and customer expectation towards homestay. The analysis, in fact, will be divided into two methods which are percentage and correlation analyses. The result of this research revealed that homestay had already provided customers with reasonable prices in good locations. Antithetically, activities that they offered still could not have met the customer’s requirements. Homestay providers should prepare additional activities such as village tour, local attraction tour, village daily life experiences, local ceremony participation, and interactive conversation with local people. Moreover, the results indicated that a price was the most important factor for choosing homestay.

Keywords: ecotourism, homestay, marketing, sufficiency economic philosophy

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Authors: Akshata Patel, Reenu Singh

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This paper focuses on current and upcoming fashion trends and global impact on the fashion industry due to the COVID-19 pandemic. The pandemic has had a major impact on the fashion industry worldwide. At the same time, the fashion market also faces challenges in consumer demand. As the supply chain and distribution channels are interconnected, this outbreak has a global impact due to travel restrictions and raw materials shortages. Given that this particular period represents an unprecedented market situation with almost no prior research on how the industry will recover from such a crisis and mold back to its original form, this research aims to propose new possibilities by evaluating the framework of specific segments. Based on the analysis and extensive literature review, the study develops a conceptual model that will illustrate the various connections among the different segments of the fashion industry. The findings provide actionable considerations for fashion industry pupils when implementing appropriate strategies to prevent unfavourable outcomes during times of crisis, such as the COVID-19 outbreak.

Keywords: COVID-19, fashion industry, global impact, new possibilities, pandemic

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Authors: Nadia Fatima Zahra Malki

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The world has witnessed a great revolution in to field of technology and communication, especially after the opening of markets (globalization). This has led to a change from traditional marketing, which depends on direct selling and buying, to electronic marketing; consequently, different corporations have adopted this new concept so as to gain time, effort and money for the sake of the customer’s satisfaction. The main reason for this study is to know the impact of electronic marketing on consumer satisfaction in the fields of communication through practical studies of Ooredoo customers, where the descriptive analytical method was used with statistics to analyze the results of the survey. It concluded that e-marketing effectively contributes to customer satisfaction.

Keywords: e-marketing, consumer, consumer behavior, satisfaction

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Authors: Harneet Walia, Morteza Zihayat

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Customer acquisition has become one of the critical issues of any business in the 21st century; having a healthy customer base is the essential asset of the bank business. Term deposits act as a major source of cheap funds for the banks to invest and benefit from interest rate arbitrage. To attract customers, the marketing campaigns at most financial institutions consist of multiple outbound telephonic calls with more than one contact to a customer which is a very time-consuming process. Therefore, customized direct marketing has become more critical than ever for attracting new clients. As customer acquisition is becoming more difficult to archive, having an intelligent and redefined list is necessary to sell a product smartly. Our aim of this research is to increase the effectiveness of campaigns by predicting customers who will most likely subscribe to the fixed deposit and suggest the most suitable month to reach out to customers. We design a Time Aware Upsell Prediction Framework (TAUPF) using two different approaches, with an aim to find the best approach and technique to build the prediction model. TAUPF is implemented using Upsell Prediction Approach (UPA) and Clustered Upsell Prediction Approach (CUPA). We also address the data imbalance problem by examining and comparing different methods of sampling (Up-sampling and down-sampling). Our results have shown building such a model is quite feasible and profitable for the financial institutions. The Time Aware Upsell Prediction Framework (TAUPF) can be easily used in any industry such as telecom, automobile, tourism, etc. where the TAUPF (Clustered Upsell Prediction Approach (CUPA) or Upsell Prediction Approach (UPA)) holds valid. In our case, CUPA books more reliable. As proven in our research, one of the most important challenges is to define measures which have enough predictive power as the subscription to a fixed deposit depends on highly ambiguous situations and cannot be easily isolated. While we have shown the practicality of time-aware upsell prediction model where financial institutions can benefit from contacting the customers at the specified month, further research needs to be done to understand the specific time of the day. In addition, a further empirical/pilot study on real live customer needs to be conducted to prove the effectiveness of the model in the real world.

Keywords: customer acquisition, predictive analysis, targeted marketing, time-aware analysis

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Authors: Stephan Schiffer, Andreas Kain, Philipp Wilde, Maximilian Helbing, Bernard Bäker

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Automobile manufacturers progressively focus on a downsizing strategy to meet the EU's CO2 requirements concerning type-approval consumption cycles. The reduction in naturally aspirated engine power is compensated by increased levels of turbocharging. By downsizing conventional engines, CO2 emissions are reduced. However, it also implicates major challenges regarding longitudinal dynamic characteristics. An example of this circumstance is the delayed turbocharger-induced torque reaction which leads to a partially poor response behavior of the vehicle during acceleration operations. That is why it is important to focus conventional drive train design on real customer driving again. The currently considered dynamic maneuvers like the acceleration time 0-100 km/h discussed by journals and car manufacturers describe longitudinal dynamics experienced by a driver inadequately. For that reason we present the realization and evaluation of a comprehensive proband study. Subjects are provided with different vehicle concepts (electrified vehicles, vehicles with naturally aspired engines and vehicles with different concepts of turbochargers etc.) in order to find out which dynamic criteria are decisive for a subjectively strong acceleration and response behavior of a vehicle. Subsequently, realistic acceleration criteria are derived. By weighing the criteria an evaluation metric is developed to objectify customer-oriented transient dynamics. Fully-electrified vehicles are the benchmark in terms of customer-oriented longitudinal dynamics. The electric machine provides the desired torque almost without delay. This advantage compared to combustion engines is especially noticeable at low engine speeds. In conclusion, we will show the degree to which extent customer-relevant longitudinal dynamics of conventional vehicles can be approximated to electrified vehicle concepts. Therefore, various technical measures (turbocharger concepts, 48V electrical chargers etc.) and drive train designs (e.g. varying the final drive) are presented and evaluated in order to strengthen the vehicle’s customer-relevant transient dynamics. As a rating size the newly developed evaluation metric will be used.

Keywords: 48V, customer-oriented driving dynamics, electric charger, electrified vehicles, vehicle concepts

Procedia PDF Downloads 406

Authors: Suman Podder

Abstract:

As Australian ‘Open Banking’ allows customers to share their financial data with accredited Third-Party Providers (‘TPPs’), it is necessary to evaluate whether the regulators have achieved the balance between protecting customer data privacy and promoting data-related innovation. Recognising the need to increase customers’ influence on their own data, and the benefits of data-related innovation, the Australian Government introduced ‘Consumer Data Right’ (‘CDR’) to the banking sector through Open Banking regulation. Under Open Banking, TPPs can access customers’ banking data that allows the TPPs to tailor their products and services to meet customer needs at a more competitive price. This facilitated access and use of customer data will promote innovation by providing opportunities for new products and business models to emerge and grow. However, the success of Open Banking depends on the willingness of the customers to share their data, so the regulators have augmented the protection of data by introducing new privacy safeguards to instill confidence and trust in the system. The dilemma in policymaking is that, on the one hand, lenient data privacy laws will help the flow of information, but at the risk of individuals’ loss of privacy, on the other hand, stringent laws that adequately protect privacy may dissuade innovation. Using theoretical and doctrinal methods, this paper examines whether the privacy safeguards under Open Banking will add to the compliance burden of the participating financial institutions, resulting in the undesirable effect of stifling other policy objectives such as innovation. The contribution of this research is three-fold. In the emerging field of customer data sharing, this research is one of the few academic studies on the objectives and impact of Open Banking in the Australian context. Additionally, Open Banking is still in the early stages of implementation, so this research traces the evolution of Open Banking through policy debates regarding the desirability of customer data-sharing. Finally, the research focuses not only on the customers’ data privacy and juxtaposes it with another important objective of promoting innovation, but it also highlights the critical issues facing the data-sharing regime. This paper argues that while it is challenging to develop a regulatory framework for protecting data privacy without impeding innovation and jeopardising yet unknown opportunities, data privacy and innovation promote different aspects of customer welfare. This paper concludes that if a regulation is appropriately designed and implemented, the benefits of data-sharing will outweigh the cost of compliance with the CDR.

Keywords: consumer data right, innovation, open banking, privacy safeguards

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Authors: Riktesh Srivastava

Abstract:

Online Shopping have established an astonishing evolution in the last few years. And it is now apparent that B2C architecture is becoming progressively imperative channel for even traditional brick and mortar type traders as well. In this completion knowing customers and predicting behavior are extremely important. More important, when any customer logs onto the B2C architecture, the traces of their buying patterns can be stored and used for future predictions. Such a prediction is called Customer Lifetime Value (CLV). Earlier, we used Net Present Value to do so, however, it ignores two important aspects of B2C architecture, “market risks” and “big amount of customer data”. Now, we use RFM- Recency, Frequency and Monetary Value to estimate the CLV, and as the term exemplifies, market risks, is well sheltered. Big Data Analysis is also roofed in RFM, which gives real exploration of the Big Data and lead to a better estimation for future cash flow from customers. In the present paper, 6 factors (collected from varied sources) are used to determine as to what attracts the customers to the B2C architecture. For these 6 factors, RFM is computed for 3 years (2013, 2014 and 2015) respectively. CLV and Revenue are the two parameters defined using RFM analysis, which gives the clear picture of the future predictions.

Keywords: CLV, RFM, revenue, recency, frequency, monetary value

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Authors: Samaneh Pouyanfar, Michael Oliff

Abstract:

The industry of home appliances may beone of theindustries which has the highest competition, and actually what can guarantee the survival of this industry is discovering the superior services. A trend to provide quality products and services plays an important role in this industry because discovering the services is counted as a vital affair for Manufacturing Organizations’ survival and profitability. Given the importance of the topic, this paper attempts to investigate the relative priority of the factors influencing the customer satisfaction in gaining the competitive advantage in Pars-Khazar Company. In sum, 96 executives of Pars-Khazar Company where investigated in a census. For this purpose, after reviewing the research literature and performing deep interviews between pundits and experts active in the industry, the research questionnaire was made based on variables affecting customer satisfaction and components determining business competitive advantage. Determining the content validity took place by judgement of the experts. The reliability of each structure was measured based on Cronbach’s alpha coefficient. Since the value of Cronbach's alpha was higher than 0.7 for each structure, internal consistency of statements was high and the reliability of the questionnaire was acceptable. The data analysis was also done with Kulmgrf-asmyrnf test and Friedman test using SPSS software. The results showed that in dimension of factors affecting customer satisfaction, the History of trade name (brand), Familiarity with the product brand, Brand reputation and Safety have the highest value of priority respectively, and the variable of firm growth has the highest value of priority among the components determining the performance of competitive advantage.

Keywords: customer satisfaction, competitive advantage, brand history, safety, growth

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Authors: Tsegay Teklebrhan Gebremariam, Zhiliang, Arjan Jonker

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The study investigated that using corn gluten (CG) instead of cornmeal (CM) increased dietary sulfur shifted H₂ metabolism from methanogenesis to alternative sink and modulated microbiome in the rumen as well as hindgut segments of goats. Ruminal fermentation, CH₄ emissions and microbial abundance in goats (n = 24). The experiment was performed using a randomized block design with two dietary treatments (CM and CG with 400 g/kg DM each). Goats in CG increased sulfur, NDF and CP intake and decreased starch intake as compared with those in CM. Goats that received CG diet had decreased dissolved hydrogen (dH₂) (P = 0.01) and dissolved methane yield and emission (dCH₄) (P = 0.001), while increased dH₂S both in the rumen and hindgut segments than those fed CM. Goats fed CG had higher (p < 0.01) gene copies of microbiota and cellulolytic bacteria, whereas starch utilizing bacterial species were less in the rumen and hindgut than those fed CM. Higher (P < 0.05) methanogenic diversity and abundances of Methanimicrococcus and Methanomicrobium were observed in goats that consumed CG, whilst containing lower Methanobrevibacter populations than those receiving CM. The study suggested that goats fed corn gluten improved the gene copies of microbiota and fibrolytic bacterial species while reducing starch utilizing species in the rumen and hindgut segments as compared with that fed cornmeal. Goats consuming corn gluten had a more enriched methanogenic diversity and reduced Methanobrevibacter, a contributor to CH₄ emissions, as compared with goats fed CM. Corn gluten could be used as an alternative feed to decrease the enteric CH₄ emission in ruminant production.

Keywords: dissolved gasses, methanogenesis, microbial community, metagenomics

Procedia PDF Downloads 158

Authors: Dim En Nyaung, Thin Lai Lai Thein

Abstract:

Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: opinion mining, opinion summarization, sentiment analysis, text mining

Procedia PDF Downloads 332

Authors: Ayedh Alqahtani

Abstract:

Many construction firms in Saudi Arabia dedicated to building projects agree that the most important factor in the real estate market is the value that they can give to their customer. These firms understand the value of their client in different ways. Value can be defined as the size of the building project in relationship to the cost or the design quality of the materials utilized in finish work or any other features of building rooms such as the bathroom. Value can also be understood as something suitable for the money the client is investing for the new property. A quality tool is required to support companies to achieve a solution for the building project and to understand and manage the customer’s needs. Quality Function Development (QFD) method will be able to play this role since the main difference between QFD and other conventional quality management tools is QFD a valuable and very flexible tool for design and taking into the account the VOC. Currently, organizations and agencies are seeking suitable models able to deal better with uncertainty, and that is flexible and easy to use. The primary aim of this research project is to incorporate customer’s requirements in the conceptual design of construction projects. Towards this goal, QFD is selected due to its capability to integrate the design requirements to meet the customer’s needs. To develop QFD, this research focused upon the contribution of the different (significantly weighted) input factors that represent the main variables influencing QFD and subsequent analysis of the techniques used to measure them. First of all, this research will review the literature to determine the current practice of QFD in construction projects. Then, the researcher will review the literature to define the current customers of residential projects and gather information on customers’ requirements for the design of the residential building. After that, qualitative survey research will be conducted to rank customer’s needs and provide the views of stakeholder practitioners about how these needs can affect their satisfy. Moreover, a qualitative focus group with the members of the design team will be conducted to determine the improvements level and technical details for the design of residential buildings. Finally, the QFD will be developed to establish the degree of significance of the design’s solution.

Keywords: quality function development, construction projects, Saudi Arabia, quality tools

Procedia PDF Downloads 124