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More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
\n'}],latestNews:[{slug:"intechopen-maintains-position-as-the-world-s-largest-oa-book-publisher-20201218",title:"IntechOpen Maintains Position as the World’s Largest OA Book Publisher"},{slug:"all-intechopen-books-available-on-perlego-20201215",title:"All IntechOpen Books Available on Perlego"},{slug:"oiv-awards-recognizes-intechopen-s-editors-20201127",title:"OIV Awards Recognizes IntechOpen's Editors"},{slug:"intechopen-joins-crossref-s-initiative-for-open-abstracts-i4oa-to-boost-the-discovery-of-research-20201005",title:"IntechOpen joins Crossref's Initiative for Open Abstracts (I4OA) to Boost the Discovery of Research"},{slug:"intechopen-hits-milestone-5-000-open-access-books-published-20200908",title:"IntechOpen hits milestone: 5,000 Open Access books published!"},{slug:"intechopen-books-hosted-on-the-mathworks-book-program-20200819",title:"IntechOpen Books Hosted on the MathWorks Book Program"},{slug:"intechopen-s-chapter-awarded-the-guenther-von-pannewitz-preis-2020-20200715",title:"IntechOpen's Chapter Awarded the Günther-von-Pannewitz-Preis 2020"},{slug:"suf-and-intechopen-announce-collaboration-20200331",title:"SUF and IntechOpen Announce Collaboration"}]},book:{item:{type:"book",id:"2123",leadTitle:null,fullTitle:"Complementary Pediatrics",title:"Complementary Pediatrics",subtitle:null,reviewType:"peer-reviewed",abstract:"Complementary Pediatrics covers complementary issues of pediatric subspecialties consisting of ophthalmologic, surgical, psychosocial and administrative issues of frequently used medications. This book volume with its 16 chapters will help get us and patients enlightened with the new developments on these subspecialties' area.",isbn:null,printIsbn:"978-953-51-0155-0",pdfIsbn:"978-953-51-6851-5",doi:"10.5772/2527",price:139,priceEur:155,priceUsd:179,slug:"complementary-pediatrics",numberOfPages:356,isOpenForSubmission:!1,isInWos:1,hash:"9a8d394d9989a6dcc3a9a867f0af3a6b",bookSignature:"Öner Özdemir",publishedDate:"March 16th 2012",coverURL:"https://cdn.intechopen.com/books/images_new/2123.jpg",numberOfDownloads:78848,numberOfWosCitations:29,numberOfCrossrefCitations:9,numberOfDimensionsCitations:50,hasAltmetrics:1,numberOfTotalCitations:88,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 6th 2011",dateEndSecondStepPublish:"May 4th 2011",dateEndThirdStepPublish:"September 8th 2011",dateEndFourthStepPublish:"October 8th 2011",dateEndFifthStepPublish:"February 7th 2012",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,editors:[{id:"62921",title:"Dr.",name:"Öner",middleName:null,surname:"Özdemir",slug:"oner-ozdemir",fullName:"Öner Özdemir",profilePictureURL:"https://mts.intechopen.com/storage/users/62921/images/system/62921.jfif",biography:"Prof. Dr. Öner Özdemir was born in Alaplı, Zonguldak, Turkey in 1965. 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His clinical fellowship training was finished at Pediatric Allergy/Immunology division in Louisiana State University, Health Sciences Centre, New Orleans, LA.\r\nDr. Ozdemir bench research areas are as follows: LAK-cell generation and cell-mediated cytotoxicity; human mast cell development and mast cell-mediated cytotoxicity; and apoptosis related research. \r\nHe was the first place winner of Clemens Von Pirquet Award from ACAAI at ACAAI meeting in 2005 for the best research on allergy/asthma/immunology by a fellow in training. \r\nDr. Ozdemir has more than 100 international plus 40 national publications, as well as 160 international and 140 national presentations, and more than 9 chapters related to my research areas. \r\nCurrently, he works as a chief of pediatrics associated with the division of pediatric allergy/immunology at Sakarya University, Medical School, Teaching and Training Hospital, Adapazarı, Sakarya, Turkey.",institutionString:"Sakarya University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"3",institution:{name:"Sakarya University",institutionURL:null,country:{name:"Turkey"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1112",title:"Pediatric Surgery",slug:"pediatric-surgery"}],chapters:[{id:"30824",title:"Pediatric Ophthalmology / Eye and Disorders",doi:"10.5772/33248",slug:"pediatric-ophthalmology-eye-and-disorders",totalDownloads:8864,totalCrossrefCites:1,totalDimensionsCites:2,signatures:"Hikmet Basmak, Nilgun Yildirim, Seyhan Topbas, Ahmet Ozer, Nazmiye Erol, Huseyin Gursoy and Afsun Sahin",downloadPdfUrl:"/chapter/pdf-download/30824",previewPdfUrl:"/chapter/pdf-preview/30824",authors:[{id:"94622",title:"Dr.",name:"Meselik Saglik Ve",surname:"Egitim Vakfi",slug:"meselik-saglik-ve-egitim-vakfi",fullName:"Meselik Saglik Ve Egitim Vakfi"},{id:"98268",title:"Dr.",name:"Huseyin",surname:"Gursoy",slug:"huseyin-gursoy",fullName:"Huseyin Gursoy"},{id:"98269",title:"Prof.",name:"Nilgun",surname:"Yildirim",slug:"nilgun-yildirim",fullName:"Nilgun Yildirim"},{id:"98271",title:"Prof.",name:"Seyhan",surname:"Topbas",slug:"seyhan-topbas",fullName:"Seyhan Topbas"},{id:"98274",title:"Prof.",name:"Ahmet",surname:"Ozer",slug:"ahmet-ozer",fullName:"Ahmet Ozer"},{id:"98277",title:"Dr.",name:"Nazmiye",surname:"Erol",slug:"nazmiye-erol",fullName:"Nazmiye Erol"},{id:"98278",title:"Dr.",name:"Afsun",surname:"Sahin",slug:"afsun-sahin",fullName:"Afsun Sahin"}],corrections:null},{id:"30825",title:"Acquired Cryptorchidism: What Should We Know? 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\r\n\tOrganic synthesis has always been one of the central topics of research for the scientific community in the academic laboratories and industrial world. Many striking journal articles and remarkable reviews and books have been published in the past year describing the practicability and applications of the subject demonstrating the importance of organic synthesis. In the present book, we will be putting together the topics in organic synthesis which may include but not limited to, (1) the basic terms and concepts, (2) various organic reactions including reduction, oxidation, addition, elimination, rearrangements, and cycloadditions, (3) Total Synthesis of Natural products, (4) transition metal catalysts, organocatalysts, enzymes and biotransformations, (5) applications in medicinal chemistry and drug design and development, (6) purification methods and characterization techniques, etc. To set a limit and to increase the scope of the book, author(s) are encouraged to send the chapters that include selected examples with practical applications and good yielding reactions reported within the past decade. Older topics with significant findings or their essence to prepare the foundation may be included in the chapter are welcomed as well.
",isbn:null,printIsbn:"979-953-307-X-X",pdfIsbn:null,doi:null,price:0,priceEur:null,priceUsd:null,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"f3bbbd989d0896f142d317ccb8abcc35",bookSignature:"Dr. Prashant S Deore",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/8807.jpg",keywords:"Natural Product Synthesis, Organic Reaction Mechanism, Stereoselective synthesis, Chirality, C-H Functionalization, Cross-Coupling Reactions, Heterogeneous Catalysis, Homogeneous Catalysis, Green Synthesis, Green Solvents and Reagents, Bioorganic synthesis, Click Chemistry",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"December 10th 2018",dateEndSecondStepPublish:"January 14th 2019",dateEndThirdStepPublish:"March 15th 2019",dateEndFourthStepPublish:"May 20th 2019",dateEndFifthStepPublish:"July 19th 2019",remainingDaysToSecondStep:"2 years",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:null,coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"251769",title:"Dr.",name:"Prashant",middleName:"S",surname:"Deore",slug:"prashant-deore",fullName:"Prashant Deore",profilePictureURL:"https://mts.intechopen.com/storage/users/251769/images/system/251769.png",biography:"Dr. Prashant S. Deore was born in India. He received a Master’s degree in organic chemistry from Pune University in 2007. In the same year, he qualified with the SET and CSIR-NET (JRF) and joined in the group of Prof. Narshinha P. Argade for the doctoral studies in National Chemical Laboratory, India. In 2014, he awarded with a Ph. D. in Chemistry and was a recipient of the 2nd prize in “2014 Eli Lilly and Company Asia Outstanding Thesis Awards”. In July 2014 he moved to Canada and joined as a postdoctoral researcher in the group of Prof. Richard Manderville at the University of Guelph, Canada. Presently, Dr. Deore is working on the collaborative project between the University of Guelph and Aterica health Inc., and providing consulting to the company. 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From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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The purpose of this chapter is to introduce the reader to the use and determination of heat transfer properties allowing a real approximation to the phenomenon under study.
Foods are complex systems that exhibit anisotropic behavior, which hinders real modeling of the phenomena that occurs within them or their interaction with the environment.
After several years of study of thermal phenomena in foods, we have identified some routes and mathematical algorithms, which are modeled on personal computers with Intel architecture. We have also corroborated the results of these models with real data of canning, pasteurizing, cooking and freezing experiments, showing less than 3% deviation between theoretical and real value.
Example Case:
A computer-aided engineering model is described. This model is capable of simulating the thermal sterilization of canned foods. The use of the model to find optimum processing conditions, physical properties and container geometry is reported.
This example describes the use of thermal properties in the development of computer models that simulate conduction heat transfer in canned foods. These models can be used to mix physical and thermal properties of the material under study for the prediction of the product temperature and processing time, considering different geometries from the metallic containers for foods and conditions of operation in pressure and temperature of the steam. The results obtained in the simulations are compared with the real processes of canning in the pilot plant. A second advantage is that the retort’s temperature need not to be held constant, but can vary in any prescribed manner throughout the process and the model will predict the correct product temperature history at the can’s center. The use of these models has become invaluable for simulating the process conditions in sterilizer system. Another important application of these models is the rapid evaluation of an unscheduled process deviation, such as when an unexpected drop in retort temperature occurs during the process. The model can quickly predict the product center temperature history in response to such a deviation, and calculate the delivered sterilizing value (Fo) comparison with the target value specified for the product. Specific objectives of this chapter are to briefly describe how the model was developed and to use it in process optimization and on-line computer control applications.
Generally, thermal processing is not meant to destroy all microoganisms in a packaged product. Such a process would result in low product quality due to the long heating required. Instead, the pathogenic microorganisms in a hermetically sealed container are destroyed an enviroment is created inside the package which does not support the growth of spoilage type microoganisms. In order to determine the extent of heat treatment, several factors must be known [1], (1) type ab heat resistance of the target microorganisms or enzime present in the food; (2) pH of the food; (3)heating conditions; (4) thermo-physical properties of the food and the container shape and size; and (5) storage conditions following the process.
Foods have different microoganisms and/or enzimes that the thermal process is designed to destroy. In orden to determine the type of microoganims on which the process should be based several factors must be considered. With reference to thermal processing, the most important distinction in pH classication is the dividing line between acid and low acid food. Most laboratories deading with thermal processing devote special attention to Clostridium botulinum which is a highly heat resistance, rod-shaped, spore-forming, anaerobic pathogen that produce botulism toxin. It has been generally accepted than C.botulinum does not grow and produce toxins below a pH of 4.6. Hence, pH as 4.5 is taken the dividing line between the low acid and acid foods. There are other microorganisms, for example Bacillus thermoacidurans, B. stearotermophilus, and C.thermosaccolyticum, which are more heat resistance than C.butulinum. These are generally thermophilic in nature (50-55ºC), and hence are not of much concern if the processed cans are stored at temperatures below 30ºC.
The phrase “minimal thermal process” was introduced by tha US Food and Drugs Administrations in 1977 and defined as “the application of heat to food, either before or after sealing in a hermetically sealed container, for a period of time and at temperature acientifically determined to be adequate to ensure the destruction of microorganims of public health concern”[2].
The C.butulinum is a microorganims of public health low-acid foods and due to this high-heat resistance, temperatures of 115-125ºC are commonly employed for processing these foods.With reference to the acid and medium-acid foods, the process is usuallly based on the heat-resistant spoilage-type vegetative bacteria or enzyme which are easily destroyed even at temperatures below 100ºC. The thermal processes for such foods are therfore normally carried out in boiling water.
The thermal resistance of microorganisms (vegetative cells or spores) is dependent upon a number of factors: 1) the growth characteristics of the microorganisms, 2) the nature of the food in which the microorganisms are heated, and 3) the kind of food in which the heated microorganisms are allowed to grow. Because of the variability of any biological entity, thermobacteriology is a highly complex science, and variations in any of these factors can affect the heat resistance of microorganisms.
The amount of heat required to destroy microorganisms in a product can be determined through thermal death time (TDT) tests. TDT tests are conducted by thermobacteriologists in a laboratory. Very few food processing establishments have the facilities to conduct TDT tests on-site.
The instruments and equipment used for TDT tests include TDT retorts, tubes, and/or cans; three-neck flask, oil baths, sealed plastic pouches, and/or capillary tubes. The equipment and instrumentation used will depend on the type of product being tested – whether it is low-acid, acidified, thick puree, solid or a liquid. TDT tests involve heating a known amount of microorganisms in a buffer solution or food at several temperatures and for several time intervals at each temperature. The results from the TDT tests are used to calculate D- and z-values. These values are used to define the heat resistance of the microorganisms of concern.
In conducting TDT tests, the thermal characteristics (D- and z-values) of the microorganisms will be determined. The D-value is defined as the time at a particular temperature required to reduce a known number of microorganisms by 90% or to result in a 1-log reduction. This is also termed the decimal reduction time because exposure for this length of time decreases the population by 90%, thus shifting the decimal point in the number of microorganisms remaining one place to the left. For example, if you had 100,000 spores and if exposing them to a temperature of 240°F for 3 minutes reduced the count to 10,000 spores, the D240°F would be 3 minutes.
The D-value decreases as the temperature increases, since it takes less time to destroy the microorganisms at the higher temperature. By determining the D- values at various temperatures, a z-value can be determined from the slope of the line that results from plotting the log of D-values versus temperature (Figure 1a). The z-value, indicative of the change in the death rate based on temperature, is the number of degrees between a 10-fold changes (1 log cycle) in an organism’s resistance (Figure 1b). As an example, suppose that z = 18°F and D232°F = 3 minutes. The D250°F would be 0.3 minutes. (Because 232°F + 18°F = 250°F and 3 minutes / 10 = 0.3 minutes.) Both D- and z-values are indirectly used to establish processing conditions.
A) Typical survivor curve. (B) A typical thermal resistance curve.
In other words the D value represents a heating time that causes 90% destruction of the existing microbial population. Graphically, this represents the time between which the survival curve passes through one logarithmic cycle (figure 1). Mathematically
Where a and b represent the survivor counts following heating for t1 and t2 min, respectively.
Using regression techniques, z value can be obtained as the negative reciprocal slope of the thermal resistance curve (regression of log D values vs. temperature). Mathematically
Where D1 and D2 are D values at T1 and T2 respectively. The D values at any give temperature can be obtained from a modified formulation of the above equation using a reference D value (D0 at a reference temperature, T0 usually 250ºF for thermal sterilization).
Equations 3 also can be written with reference to TDT values and z values can be obtained from:
Where TDT1 and TDT2 are TDT values at T1 and T2 respectively.
A typical TDT curve
Graphically, as with the D value approach, the z values can be obtained as the negative reciprocal slope of log TDT vs. temperature curve (Figure 2). When using this approach, it is advisable to plot the longest survivor time and shortest destruction time (on logarithmic scale) vs. temperature (linear scale). The regression line could be necessary to make sure that the TDT curve is above all survivor data point. The TDT curve should be parallel to the general trend of the survival and destruction points.
Lethality (F value) is a measure of the treatment or sterilization processes. In order to compare the relative sterilization capacities of heat processes, a unit of lethality needs to be established. For convenience, this is defined as an equivalent heating of 1 min at a reference temperature, which is usually 250ºF (121.1ºC) for sterilization processes. Thus, the F value would represent a certain multiple or fraction of D values depending on the type of microorganisms; therefore, a relationship like Equation 4 also holds with reference to F value.
The Fo in this case will be the F value at the reference temperature (To).A reference TDT curve is defines as curve parallel to the real TDT or thermal resistance curve.
Almost every food, with the exception of white eggs and soda crackers, has a pH value of less than 7. Foods can be broadly categorized on the basis of their pH as high acid, acid, medium acid or low acid. Examples of each category include:
high acid (3.7) : apples, lemons, raspberries
acid (3.7 to 4.6) : oranges, olives, tomatoes (some)
medium acid (4.6 to 5.3) : bread, cheese, carrots
low acid (over 5.3) : meat, fish, most vegetables
Most micro-organisms grow best in pH range of 6.5 to 7.5. Yeasts and moulds are capable of growing over a much broader pH range than bacteria. Few pathogens will grow below pH 4.0, such as this valuable information helps in determination of food stability with respect to microbial spoilage.[3]
The heat transfer rate of a solid to a fluid can be expressed by Newton’s Law of cooling:
Where Q is the heat flow rate (J/s), As is the surface area (m2), ΔT is the temperature gradient (ºC) and the proportional constant h is the heat transfer coefficient or surface heat conductance (W/m2K). The surface heat conductance depends on the thermophysical properties of fluid and solid (density, specific heat, thermal conductivity), characteristics of the solid (shape, dimensions, surface temperature, surface roughness, outgoing fluxes), and the characteristics of fluid flow (velocity, turbulence intensity) and the systems (heat transfer equipment) [4]. Although heat transfer coefficient is not a property of food materials, but it is an important parameters for designing and controlling food processing equipment where fluids (air, nitrogen, steam, water, or oil), are used as heating, cooling, frying, freezing or cooking media.
The following data are normally obtained from the heat penetration curves and heating condition for calculation purpose (Figure 3).
Autoclaves or retorts do not reach the specified operating temperature immediately after the steam is turned on, but require a measurable heating time until they reach operating temperature. The time measure from steam -on until the unit reaches the specified operating temperature is called the “come-up period”; the objective of the heat penetration test is to obtain data for the product-container system that can be used to design a sterilization process.
In processes where water is used as the heating medium, if come-up time [CUT], is long and the size of the container is small, meaningful fh and j values for the product-container unit cannot always be contained. To have the results of a heat penetration test yield meaningful fh and jch values, the CUT should preferably be less than 0.5fh.
Heat penetration profiles of conduction and convection heating foods.
Heating curve and heating parameters (a), cooling curve and cooling parameters (b).
The true j value of a product container unit for ideal condition at time zero, the retort is turned on and is immediately at the operating temperature. For example the autoclave reaches the operating temperature of 121ºC after 5 min and remains at this temperature throughout the remainder of the process. The CUT correction indicates that 2 min of the 5-minutes CUT can be considered time as heating-medium temperature. The net result is the replacement of the first 5 min, the CUT in this example, with 0.42 x tc, which means neglecting the first 0.58 x tc. Therefore, in this example, the corrected zero is 2 min before the time when the retort reached the operating temperature and at 3 min after turning on the stream.
Thermophysical properties, a well-known group of thermal and related properties, aere necessary for the design and prediction of heat transfer operation during handling,processing, canning, and distribution of foods. In this chapter, the most important properties associated with the transfer of heat in foods are defined. Measurement techniques, available empirical equations, and mathematical models used for prediction of density, porosity, specific heat, thermal conductivity, and thermal diffusivity are presented and condensed in tables, figures, and graphs.
The micro structure in foods are essential for heat flux, how figure 5 show, when seeing the different microstructures we can see some centers that absorb and soon they generate heat, changing the heat flow to inside the food
Vortex of Koch Function
The velocity of heat flux depends on the chaotic distribution of the center, with or without complicity of flow and thermal properties which complicity or not the flow and thermal properties affecting directly inside the food. [5]
Real products are rarely of a regular geometry, have thermal properties which vary with temperature and have different heat resistances along the boundary. For example, in retorts, when condensing steam is used as the heating method, condensation may adversely affect the uniformity of heat transfer to the product surface; heat transfer to a dry surface will be very high, but the presence of a film of liquid will reduce the heat transfer rate [6]
Non-isotropic aspects of conductive cooking have been addressed, for example, by Pan et al. [7] in the modeling of the cooking of frozen hamburgers. Their approach, which involved unequal cooking to both the major external surfaces of the patty, considered the enthalpy changes associated with the melting of ice and fat as well as resulting mass transfer effects.
In the numerical data analysis to the heat equation incorporated the function of Koch, for the model heat transfer with equation:
When:
Iterative equation:
Valid for all coordinates as:
Generated, 160 x 51 iterative spaces nodes in two dimensions (X,Y)
The result of the iterative generates thermograms (8211 nodes per layer), this represents the distribution of heat inside of the cans. [8]
This case describes the use of thermal properties in the development of computer models that simulate conduction heat transfer in canned foods. These models can be used to mixture physical and thermal properties of the material to predict the product temperature and processes time, considering different geometries from the metallic containers for foods and conditions of operation in pressure and temperature of the steam; the results obtained in the simulations compare with the real processes of the canning in the pilot plant. A second advantage is that the retort temperature need not to be held constant, but can vary in any prescribed manner throughout the process and the model will predict the correct product temperature history at the can center. Use of these models has become invaluable for simulating the process conditions experience in sterilizer system, in which cans pass from the can wall. Another important application of these models is the rapid evaluation of an unscheduled process deviation, such as when an unexpected drop in retort temperature occurs during the process. The model can quickly predict the product center temperature history in response to such a deviation, and calculate the delivered sterilizing value (Fo) comparison with the target value specified for the product. Specific objectives of this chapter are to briefly describe how the model was developed and use in process optimization and on-line computer control applications.
An attempt was made to define all the physical aspects of the mathematical models developed by Ball [9], using numerical methods, the trapezoidal rule of Patashnik [10]. The disadvantage that raises these traditional methods combined is the absence of the physical properties of foods, all the preceding models to considered a heat coefficient global and deals with it like a solid or block metal, the disadvantage appears when the selected system of heat transference is by conduction or convection.
The foods do not have a linear or logical behavior but an anisotropic behavior and it is a big obstacle, therefore it is little probable to design a system that models the real phenomena of heat transference in no stationary system. The simulation model considers the following aspects:
Generation of data composed of format of tins, temperatures of operation and steam, physical properties of the product and liquid of cover.
Calculation of physical values of the canning, and verifies the conditions heat transference to the interior of the package.
It generates point to point the increase of heat in the cold point and the time necessary to arrive at the temperature of operation
It determines the increase of time in optimum conditions of sterilization.
The model consists of four main programs and an information administrator, which work sequentially according to the directives of the user, to include better the process describes next to the sequences and postulates [11].
The supposition is that it is hoped that the temperature gradients within the system are insignificant when the internal resistance to the heat transfer is small compared with the external resistance, that is to say the heat conduction by its length divided by the thermal conductivity, this relation gives origin to the adimensional Number (Biot);this number represents the relation between the form (plate and infinite cylinder) and the transitory answer, a value of Biot<0.1, it guarantees that the temperature in center does not differ more from a 5%.
For the model the number of Biot equal to 1000 guarantees that the thermal center temperature is different to the surface temperature of the product, and it should be find two functions, one for a plate and other for a cylinder, when uniting these infinite bodies generates a body finite. as shows figure to it 7. The resulting function is the sum of figures 8 and 9.
Finite cylinder
Biot number for infinite plate
Of these figures two dependent equations of Fourier are generated:
Plate:
Biot number for Infinite Cylinder
Where:
a= 0.10168949 b= -0.21732379 c= 0.3032664 d= -0.10976533 e= -0.36311129
f= -0.052222376 g= 0.21755337 h= 0.16261937 i= 0.04545908 j= 0.0045689637
With r2= 0.999859613
Cylinder:
Where:
a= 0.89545265 b= 3.193429 c= -26.00579 d= 272.66439 e= -553.74231 f=540.91268
With r2= 0.9998774042
The temperature distribution T (x, and, t) of an infinite body that submerges in a solution where St is defines as:
Adimensional temperature with boundary conditions –L1 ≤ x ≤ L1, y, -L2 ≤ x ≤ L2
Using mathematical method
The product of the solutions satisfies the original problem:
As it is a finite cylinder and it is the result of the union of an infinite cylinder and an infinite slab, the previous equation stays expressed as:
Where:
hc= convective coefficient
y= radio
As we can see the law of Fourier is implicit in the previous equations and for that reason we will only denote the use of the physical parameters in the use of these:
And
Finite Cylinder
Where tc=L2/α\n\t\t\t\t\t
α = thermal diffusivity
K= thermal conductivity
Cp= Specific heat
ρ = density appears.
One of the controversial subjects in the thermal transmission to the interior of the tin, since this allows us to know the coldest point the interior of the tin, and is there where the microorganisms proliferate and contaminates to the product, in practice it is said that if the product is solid the transference is by conduction and if he is liquid is convection, but What happens to food when liquids materials and solids materials are mixed ?, the usual thing to do is work them like solids, but this is not correct. A model for a porous and semisolid material considers the total factor of porosity of the package like:
In this way it can be compared the critical volume (Vc) of the product with the corrected volume and if the relation of the absolute value (Vt), when Vc < 3/4VT then transference is convective and when Vc ≥ 3/4VT then the transference is conductive, this empirical relation allows us to increase the time necessary to assure a suitable commercial sterilization in the cold point.
The output data of the simulation are graphical and shows the behavior through a temperature curve, which shows the temperature of operation of the retort and the thermal center. Once finalized it calculates the time necessary to equal the temperatures and to incorporate the time of commercial sterilization, as it shows the following figure 12 and table 1:
Flow Chart
Characteristic line of a process of commercial sterilization
Product | Real Time | Simulation Time | St.Deviation |
Pears | 25min | 24.99min | -0.01 |
Peach trees | 35min | 35min | 0.00 |
Seafood’s | 55 min | 55.1min | 0.10 |
Peas with Bacon | 56min | 56min | 0.00 |
Process Simulated by TDT and Real date
A Theory model, B Real flux heat in apple, C and D Real flux heat in pear
The theory analysis generates heat flux concentric like figure 13 without concerning the material, but when incorporating the Koch equation thermogram changes their form with the fig 13, B, C and D, this must to the distribution of the fiber to the interior of the food
As the results showed, the model proposed to the reader is a better approximation than the models of common usage. In practice, usually you overestimate the sterilization time for guarantee a better cleaning of pathogenic organisms and as consequence the loss of nutritional quality of the product. With the new model this is not a problem because of the better approximations in time, usage of physical properties and for the transference heat mechanisms.
In comparison, the data obtained from the simulation tests with real data obtained from experiments in the pilot plant were very close to the real data.
In computational terms, the new model showed a considerable improvement of the simulation average execution time (10 seconds.) This was compared with a normal simulation process that is about 25 minutes to 60 minutes.
An advantage of the new simulation is that from the thermograms shows second by second what is happening with the product during the process. This is not possible with the methods used normally.
As said before the average time of the simulations were low, making it a good choice for decision making in terms of industrial processes as for commercial decisions.
The numerical methods well formulated are a powerful tool for the decision making. In this case, finite differences and the finite volumes were used for the development of the work and the study that is shown in this chapter.
0.58lEffective beginning of the process; the retort come-up period varies from one process to the other and from one retort; to the other; in process evaluation procedures, about 42% of this come-up period generally considered as time at retort temperature because the product temperature increases even during this period.
α Thermal diffusivity
An Opacity factor
As Surface area (m2)
B Thermal process time; Ball-corrected for come-up period.
Cm Control node
cp Specific heat
CUT Come-up time
D Represents a heating time that 90% destruction of the existing microbial population
Γmn Emissivity angular and radial
ρ Density appears
ρaverage Density appears of average
ρsolid Density appears of solid
F Lethality value
fc Cooling rate index; the time required for the straight line portion of the cooling curve (Figure 4 b) to pass through one log cycle; also the negative reciprocal slope of the cooling rate curve.
fh Heating rate index; the time required for the straight line portion of the heating curve,(Figure 4 a) to pass through one log cycle; also the negative reciprocal slope of the heating rate curve.
Fo Initial lethality value
Fo Fourier number
G Difference between the retort temperature and food temperature at time t.
gc The value of g at the end of heating or beginning of cooling.
h Proportional constant of heat transfer coefficient
hc Convective coefficient
Ic Difference between the cooling water temperature and food temperature at the start of the cooling process.
Ih Difference between the retort temperatures at the start of the heating process
jcc Cooling rate lag factor; a factor which when multiplied by IC, locate the intersection of the extension of the straight-line portion of semilog cooling curve and the vertical line representing start of the cooling process.
jch Heating rate lag factor, a factor which, when multiplied by Ih locates the intersection of the extension of the straight-line portion of the semilog heating curve and the vertical line representing the effective beginning of the process.
k Thermal conductivity
l Come-up period; in batch processing operation, the retort requires some time for reaching the operating condition; the time from stream to when the retort reached Tr is called the come-up period
PF Porosity factor
pH Hydrogen potential
Pt Operator’s process time
Q Heat low rate
t Time (min)
T Temperature (ºC)
TDT Thermal death time
Te Centre temperature
Tic Food temperature when cooling started
Tih Initial food temperature when heating is started.
To Initial temperature
Tpic Pseudo-initial temperature during cooling; temperature indicated by the intersection of the extension of the cooling curve and the vertical line representing the start of cooling
Tpih Pseudo-initial temperature during heating; temperature indicated by the intersection of the extension of the heating curve and the vertical line representing the effective beginning of the process (0.58l).
Tr Retort temperature
Tw Cooling water temperature
Vc Critical volume
Vt Absolute volume
x Length (m)
y Radio (m)
Z Is the change in death rate based on temperature
“Any sufficiently advanced technology is indistinguishable from magic.”
-Arthur C Clarke
Today, 55% of the world’s population lives in urban areas, and this proportion is expected to reach 68% by 2050 [1]. City governments face the challenge of producing wealth, innovation, health, and sustainability [2], but with an increase in urban populations, these challenges become harder for city governments to manage. For this reason, instead of continuing to use old-fashioned methods, some cities have applied updated, innovative methods to manage such issues in smarter ways [3], much as we do in our daily lives. We have moved from using “dumb” technologies (e.g., a road atlas or telephone) to interacting with “smart” technologies (e.g., personalized journey planning apps on smart phones) that “exist to help us, serve us, to make our lives easier and more interesting” [4].
As internationalization has become a widely discussed topic in recent years [5], the problem of overcrowding of cities is considered a global issue, and smart city applications have spread rapidly worldwide [2]. These applications not only enable city governments to facilitate the routine functions of individuals, buildings, and traffic systems but also enable them to monitor, understand, analyze, and plan cities to improve their efficiency, equity, and quality of life in real time [6]. The concept “smart,” therefore, means the ability to manage the complexity through Big Data, which comes from a variety of sources in a huge volume and in a rapid way. As an example, in their daily lives, individuals check their social media accounts from mobile devices and share or like posts. They also read personalized news and check traffic jams. They then check their e-mail when they arrive at their offices. At lunchtime, they order food using online applications, and they watch personalized videos during free time. In other words, individuals produce a great deal of personal data and consume many more services based on that data. Thus, they also desire cities that support this lifestyle [7].
For instance, in Milton Keynes, a large town in the middle of England, the rapid expansion of the Internet together with young and technically inclined population gave rise to the concept of “smart cities.” This included the application of technology, especially Big Data principles, to improve residents’ quality of life. Such applications ranged from waste management to public transportation [8]. Now, many more cities, such as London, Stockholm, Amsterdam, Vienna, Luxembourg, Turku, Eindhoven, and Montpellier, have adopted a “smart” approach. The smart city theme also provides a city more stable and higher brand equity than green and creative themes [9]. In a project conducted at the Vienna University of Technology, six indicators of smart cities were identified:
“Smart economy,” including competitive components, such as innovation, entrepreneurship, and productivity
“Smart people,” which is the result of ethnic or social diversity and related to online education to raise social capital and qualification
“Smart governance,” such as e-government, which can include all parties in transparent decision-making processes
“Smart mobility,” which includes transportation planned using information and communications technologies (ICT)
“Smart environment,” which encourages cities to use energy efficiently by employing innovative technologies, such as solar energy and other renewable sources
“Smart living,” which refers to systems that improve quality of life, such as services and public safety tools [10]
These components are associated with different aspects of urban life: (1) industry, (2) education, (3) e-democracy, (4) logistics and infrastructure, (5) efficiency and sustainability, and (6) security and quality, respectively [11, 12].
This study is focused on smart mobility and examines the case of Istanbul New Airport, which officially opened on 29 October 2018. With a capacity of 200 million annual passengers and 3500 flights per day, Istanbul New Airport is the first smart airport of its size [13].
As an indicator of smart cities in terms of logistics and infrastructure, smart mobility requires urban planning that shifts the focus of transportation modes from individual to collective through the extensive use of ICT [14]. Smart mobility is concerned with local and global accessibility, ICT infrastructure, and innovative and sustainable transport systems [15]. Moreover, it should serve individuals’ needs by reducing time spent traveling and helping travelers avoid unnecessary travel altogether [16]. To provide these outputs, smart mobility should [17] accomplish the following goals:
Use technology to generate and share data, information, and knowledge that influence decisions.
Use technology to enhance vehicles, infrastructure, and services.
Derive improvements for transport system operators, users, and shareholders.
In certain situations, IT-supported service experiences can enhance customer satisfaction significantly [18]. Therefore, customer journey maps can be analyzed to observe the effects of technologies on customers’ experiences with the provided services.
Shorter life cycles make products and services more commoditized. Therefore, the differentiation has shifted from the offerings themselves to their providers that create experiences related with the acquisition, use, and maintenance of these offerings. People are naturally inclined to prefer pleasant, special experiences that have important lasting effects [19]. Thus, the opportunity for new revenue growth depends not only on driving sales of existing goods and services but on creating experiences for which customers are willing to pay [20]. Experiences can be conceptualized as “events that engage individuals in a personal way” [21] or as “enjoyable, engaging, memorable encounters for those consuming these events” [22], so creating strong customer experiences is a leading objective for management [23] to create competitive advantage [24].
Given the current progress of technology, it is possible to use it to develop customer experiences. For instance, in the fashion industry, information technologies enhance customer experiences by creating interactive and exciting shopping experiences [25]. In the banking industry, the increase of the Internet services and automated teller machines (ATMs) in various locations provides more services and more comfortable customer experiences than before [26]. In addition to B2C context, technology is used also to create B2B customer experiences, such as salespeople’s use of information technology [27].
In addition to enhancing experiences, technology advancement also provides multiple ways for customers to interact with product and service providers. These interactions are crucial to creating superior customer experiences [28]. To depict the events through which customers may interact with a service organization, academics and practitioners use a strategic management tool called customer journey mapping (CJM) [29].
Cities are considered smart when “investments in human and social capital and traditional (transport) and modern (ICT) communication infrastructure fuel sustainable economic growth and a high quality of life, with a wise management of natural resources, through participatory governance” [30]. As a dimension of smart city planning, smart mobility is considered in this study. Smart mobility can be summarized as planning and controlling transport systems through the extensive use of ICT. This kind of system has recently been applied in the building of Istanbul New Airport.
Airport information systems are divided into seven sections [31]:
Flight planning and operation
Passenger process
Business administration
Security
Facility management
Business center and airport management
Contact and information
Recently, airports in the Middle East and in Istanbul have begun to compete with European airports to create a “global hub” for connecting (transfer) passengers [32]. With the increased capacity and technologies developed at Istanbul New Airport, an improved customer experience would provide a competitive advantage. Thus, CJM is proposed in this study to depict customer experiences based on the technologies adapted at Istanbul New Airport.
The format used by Rosenbaum et al. was considered when creating the CJM [29]. On the CJM’s horizontal axis, the customer touch points take place according to a process timeline. The timeline is also divided into three periods: pre-service, service, and post-service. The pre-service period refers to customer experiences that occur before a service begins. The service period refers to customer experiences during the actual service. Finally, the post-service period refers to customer experiences occurring after the service [29]. In parallel with this process, a CJM can represent customer experiences prior to going to the airport, at the airport, and after leaving the airport, respectively.
To develop a CJM for Istanbul New Airport, customer touch points are determined first to build the CJM’s horizontal axis. The general limitation of CJM indicated by Rosenbaum et al. was that a common underlying assumption for customer touch points was the consideration that each touch point was equally important to the planning process; however, not all customers experience all touch points [29]. Thus, 62 students with previous flight experiences were recruited from two undergraduate marketing classes at Marmara University using a convenience sampling method. As the Istanbul New Airport was not operating at full capacity at the time of the study, the selection criterion was limited to participants’ previous flight experience at other airports in Istanbul (Istanbul Atatürk Airport or Istanbul Sabiha Gökçen Airport). To determine a unique CJM, only flights departing from the airports were considered. The main assumption for this approach was that passengers spend more time—or, in other words, they experience more—at the departure airport.
As discussed previously, the main assumption of CJM is that each passenger’s touch points are considered to be of equal importance. To address this limitation, the students were asked to indicate the first touch points that came to mind regarding the departure airports in Istanbul. As they all experienced different touch points, all the steps gathered from the students are listed in Table 1 to create a complete list of customer journey touch points. The percentages of listed touch points are indicated next to them. At the end of this step, a total of 33 touch points was identified by the respondents. Of the steps, 7 occurred during the pre-service period (before passengers arrive to the airport), 20 occurred during the service period (when passengers are at the airport), and 6 occurred during the post-service period (after passengers leave the airport). After the collection of the touch points for Istanbul Airport as a departure airport, two marketing professors from Marmara University checked them for a potential missing point.
(% listed) | |
---|---|
Pre-service period (before passengers arrive at the airport) | |
Please list your pre-service (before going to the airport) touch points with the airport (such as “seeing an advertisement on a street billboard about the airport”) | |
1. Preparing luggage | 1.61 |
2. Buying tickets (online or through agencies) | 37.10 |
3. Transportation (public or private) to the airport | 41.94 |
4. Checking in online | 9.68 |
5. Visiting the airport’s website or mobile application | 9.68 |
6. Searching for information about facilities at the airport | 1.61 |
7. Seeing advertising (on a street billboard, a website, or a social media service) about the airport | 40.32 |
Service period (when passengers are at the airport) | |
Please list your during-service (when you are at the airport) touch points with the airport (such as “using the parking lot of the airport”) | |
1. Using the parking lot | 16.13 |
2. Security screening process | 9.68 |
3. Checking in at the airport | 19.35 |
4. Delivering luggage | 8.06 |
5. Asking for help from airport personnel (such as asking for general information or for a wheelchair) | 1.61 |
6. Eating or drinking in the cafés at the airport (including smoking rooms) | 56.45 |
7. Using an ATM to withdraw money | 1.61 |
8. Exchanging money | 1.61 |
9. Using lounge services | 9.68 |
10. Using the toilets | 9.68 |
11. Shopping at the airport | 11.29 |
12. Paying for stamp fees | 3.23 |
13. Passport control | 0 |
14. Tracking flight gates on the screens | 1.61 |
15. Going to flight gates | 4.84 |
16. Visiting duty-free stores | 11.29 |
17. Waiting in the waiting areas (such as reading a book or listening to music) | 16.13 |
18. Connecting to Wi-Fi | 8.06 |
19. Taking photos in the airport | 1.61 |
20. Boarding | 3.23 |
Post-service period (after passengers leave the airport) | |
Please list your after service (when you leave the airport) touch points with the airport (such as “talking to friends or family about the airport”) | |
1. Baggage collection (at the destination airport) | 9.68 |
2. Calling (informing) family about arrival | 12.90 |
3. Talking to friends or family about experiences at the airport | 48.39 |
4. Communicating with the airport post-services (completing a survey about experiences at the airport) | 3.23 |
5. Writing about the airport on the Internet | 1.61 |
6. Sharing photos taken at the airport on social media | 1.61 |
Istanbul New Airport’s key horizontal axis customer touch points.
The vertical axis for CJM reflects the managerial practices that enable passengers to experience each touch point in a satisfactory way [29]. As the purpose of this study is to reveal customer experiences with technology applications, only the corresponding technological application is considered regarding passenger touch points at Istanbul New Airport.
Turkish Airlines’ move from Istanbul Atatürk Airport to the Istanbul New Airport coincides with the time of this study (5–7 April 2019), so it was not possible to meet with authorities at Istanbul New Airport. However, secondary data were used to list the corresponding technological applications. A meeting was held with Ms. Hülya Zerener Gürbaşak, the corporate account manager of Technopc, which provides more than 4000 hardware products to Istanbul New Airport. These products include desktop, mini, integrated, industrial, and kiosk computers used at check-in, security, card access, and passport control points. In addition, Mr. Mertcan Tanaydı, the communication chief of İGA Istanbul Airport, provided several documents and a video [33] in which the technologies of the airport are explained in detail from a customer’s point of view.
In terms of technological infrastructure at Istanbul New Airport, three data centers support artificial intelligence (AI) and smart systems. There are 647 servers, 3267 flight displays, 4549 computers, and more than 3000 card access points. To integrate these systems, 1740 km fiber and 4500 km copper cables were used. Data from all systems can reach up to 209 million GB. A total of 708 employees works in technology support roles [33].
The main focus of the technology was a mobile application developed to assist passengers. The airport mobile application can be used before, during, and after service. It guides passengers from home to the airport, assisting with time management by considering the traffic on the road (corresponding to the pre-service touch point). Its “Where is my car?” service also helps passengers find their cars in the parking lot among 19,000 cars in the closed area and 40,000 cars in the open area (corresponding to the post-service touch point). All corresponding technological applications for the service period are listed in Table 2.
Passenger touch points during the service period | Corresponding technological applications |
---|---|
1. Using the parking lot | A total of 4500 cameras tracks the cars in the parking lot; they take photos of the cars and upload them on the airport mobile application. Visitors may find their cars by writing their license plate on the application |
2. To be controlled by security | Electronic screens at the airport entrance show wait times at the security points (based on sensors and cameras that produce heat maps showing the density of people). Accordingly, the number of security points increases or decreases. In addition, the security cameras with AI use facial recognition systems and warn security if they detect unfavorable movements in the airport |
3. Checking in at the airport | Self-check-in points allow passengers to check in for their flights and leave their luggage |
4. Delivering luggage | |
5. Asking airport personnel for help (asking for general information or for a wheelchair) | An interactive passenger assistant located at the airport enables passengers to connect to customer service and make a video call with a responsible party who can see the passenger’s flight details; the customer opens the e-ticket’s QR code and puts the mobile phone to the device. The cameras and sensors on the top scan the e-ticket’s QR code, enabling the responsible party to see both the passenger and the ticket. In this way, the responsible party can generate a personal map for the passenger from the current location to the flight gate |
6. Eating and drinking in the cafés at the airport (including lounge services and smoking rooms) | The airport location guide provided by the airport mobile application lists all facilities and stores at the airport |
7. Using an ATM to withdraw money | |
8. Exchanging money | |
9. Using lounge services | |
10. Using the toilets | |
11. Shopping at the airport | |
12. Paying for stamp fees | |
13. Passport control | The iGate-fast passport control system includes two steps. The first door is opened when the passport is scanned by a device, and the second door is opened when a passenger’s face and hand are scanned by a device and matched to the passport |
14. Tracking flight gates on screens | Flight information screens and the airport mobile application provide flight information |
15. Going to flight gates | Personalized direction is provided by the airport mobile application to the gate for the selected destination |
16. Visiting duty-free stores | Pre-ordering is available in duty-free stores, where salespeople can reserve passengers’ pre-ordered items |
17. Waiting in the waiting areas (reading a book and listening to music) | USB inputs between the seats enable passengers to charge their mobile devices |
18. Connecting to Wi-Fi | Up to 1 h of free Wi-Fi is available at the airport |
19. Taking photos in the airport | |
20. Boarding | Boarding time can be seen in the airport mobile application |
Corresponding technological applications during the service period at Istanbul New Airport.
In addition to existing technologies, new ones are planned for the airport. There will be a store offering inventions and technological products where visitors may have such experiences as flying a drone. Moreover, three types of robots will work in the airport. Service robots will assist passengers and will reply to their questions about such topics as flight gates and ticket offices. The other robots will be responsible for cleaning and safety. They will be called “İGAbots.” Another innovation will be autonomous vehicles, which will be called “İGAbus.” They will carry passengers to various places at the airport [33].
City governments today must manage increasing urban populations in smart ways. In other words, large amounts of data produced by the population should be used to create sustainable places by decreasing the chaos of overcrowding, such as traffic, pollution, and waste. One smart city dimension is smart mobility, which refers to enhancing individuals’ mobility using innovation and technology. Technology is also essential to creating customer experiences. CJM can be used to analyze touch points and their corresponding created experiences.
In this study, an attempt was made to use CJM as a tool to analyze Istanbul New Airport, one of the largest smart airports in the world, which promises memorable customer experiences. In this way, Istanbul New Airport aims to compete with other airports defined as hubs in Europe. Therefore, a customer journey was created based on a survey of 62 undergraduate students who were asked which touch points came to mind first. The corresponding technologies were indicated based on secondary data.
According to the results, the most indicated touch point from the participants was “talking to friends or family about experiences at the airport” (48.39%). However, the question should be considered to evaluate this high rate. To make the questions clear and to get more touch points, an example was provided for pre-service, service, and post-service periods. Therefore, these three questions were recalls rather than the points coming to the respondents’ minds first. Nevertheless, the findings provide evidence that touch points do not have equal importance for all passengers. Different passengers experience different touch points during their journeys, so they perceive different experiences with the technological applications.
As can be seen from the touch point-technology match, Istanbul New Airport provides experiences through technological applications for most passenger touch points. Of these technologies, the main focus is on the mobile application created to affect various points of a customer journey, including time management and considering the traffic on the road to the airport, car location in the parking lot, guides listing all the facilities and stores in the airport, flight information for the selected destination, and personalized directions to the flight gate. In addition, various technologies are used to enhance passenger experiences, such as self-check-in points, interactive passenger assistants, AI-integrated security cameras, fast passport control system, and free Wi-Fi. According to the CJM, customer experience creators should also consider passengers’ use of social media and create a strategy accordingly. Passengers like to take photos at the airport and share them on their social media accounts, so there may be several photo opportunities when they experience a new technology. In this way, passengers may share and transfer their experiences with their surroundings, leading to positive word-of-mouth communication about the airport.
Regarding the limitations of this study, as the airport was not running at full capacity, the CJM was created based on participants’ experiences at other airports in Istanbul. Therefore, a new CJM should be created after the airport begins to run at full capacity by considering the airport from both departure and arrival perspectives to extend customers’ experiences. In addition to technological applications, other managerial practices can be also included in the CJM’s vertical axis.
IntechOpen implements a robust policy to minimize and deal with instances of fraud or misconduct. As part of our general commitment to transparency and openness, and in order to maintain high scientific standards, we have a well-defined editorial policy regarding Retractions and Corrections.
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\\n\\nIntechOpen wishes to emphasize that the final decision on whether a Retraction, Statement of Concern, or a Correction will be issued rests with the Academic Editor. The publisher is obliged to act upon any reports of scientific misconduct in its publications and to make a reasonable effort to facilitate any subsequent investigation of such claims.
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\n\nIntechOpen wishes to emphasize that the final decision on whether a Retraction, Statement of Concern, or a Correction will be issued rests with the Academic Editor. The publisher is obliged to act upon any reports of scientific misconduct in its publications and to make a reasonable effort to facilitate any subsequent investigation of such claims.
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