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Barely three months into the new year and we are happy to announce a monumental milestone reached - 150 million downloads.
\n\nThis achievement solidifies IntechOpen’s place as a pioneer in Open Access publishing and the home to some of the most relevant scientific research available through Open Access.
\n\nWe are so proud to have worked with so many bright minds throughout the years who have helped us spread knowledge through the power of Open Access and we look forward to continuing to support some of the greatest thinkers of our day.
\n\nThank you for making IntechOpen your place of learning, sharing, and discovery, and here’s to 150 million more!
\n\n\n\n\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"6559",leadTitle:null,fullTitle:"Earthworms - The Ecological Engineers of Soil",title:"Earthworms",subtitle:"The Ecological Engineers of Soil",reviewType:"peer-reviewed",abstract:'This book in two sections represents the current trend of research in ecology and biology of earthworms. In section "Ecology and Diversity" the authors reported the ecological and geographical uniqueness and diversity of earthworms in different environmental terrains of Siberia and Mexico. Functional interaction between earthworms and soil nematodes was elucidated with reference to vermicomposting and agricultural systems. Importance of digital library was highlighted for inventorization and taxonomical identification of earthworms. In section "Vermicomposting" the importance of maintaining pure cultures was discussed from the viewpoint of growth rate and the reproduction of composting species. This section includes article describing the management-related issues like roles of physicochemical parameters of soil and feed mixture on growth and reproduction of commercially important species of earthworm.',isbn:"978-1-78923-397-1",printIsbn:"978-1-78923-396-4",pdfIsbn:"978-1-83881-552-3",doi:"10.5772/intechopen.71290",price:119,priceEur:129,priceUsd:155,slug:"earthworms-the-ecological-engineers-of-soil",numberOfPages:114,isOpenForSubmission:!1,isInWos:1,isInBkci:!1,hash:"0780208898e98441ccea18ea373c0708",bookSignature:"Sajal Ray",publishedDate:"June 27th 2018",coverURL:"https://cdn.intechopen.com/books/images_new/6559.jpg",numberOfDownloads:8859,numberOfWosCitations:11,numberOfCrossrefCitations:13,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:19,numberOfDimensionsCitationsByBook:1,hasAltmetrics:1,numberOfTotalCitations:43,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 24th 2017",dateEndSecondStepPublish:"November 14th 2017",dateEndThirdStepPublish:"January 13th 2018",dateEndFourthStepPublish:"April 3rd 2018",dateEndFifthStepPublish:"June 2nd 2018",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"173697",title:"Prof.",name:"Sajal",middleName:null,surname:"Ray",slug:"sajal-ray",fullName:"Sajal Ray",profilePictureURL:"https://mts.intechopen.com/storage/users/173697/images/system/173697.jpeg",biography:"Sajal Ray received an MSc in Zoology and MPhil in Environmental Science from Calcutta University, India, and a Ph.D. from Jadavpur University, India. His thesis reported the immunotoxicity of pesticides in an economically important snail of India. As a recipient of the Fogarty Visiting Fellowship, Dr. Ray carried out his postdoctoral research in cardiac pathology at the National Institutes of Health, USA. His research interest is studying the immunological responses of molluscs, sponges, crabs, and earthworms exposed to pollutants. His team is engaged in understanding the evolutionary mechanism of immunity in phylogeny. He has presented his research at various conferences including the World Congress of Malacology, Washington DC. Dr. Ray is currently a Professor of Zoology at Calcutta University.",institutionString:"University of Calcutta",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"6",institution:{name:"University of Calcutta",institutionURL:null,country:{name:"India"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"674",title:"Soil Biology",slug:"soil-biology"}],chapters:[{id:"61487",title:"Introductory Chapter: Earthworms - The Ecological Engineers of Soil",doi:"10.5772/intechopen.78264",slug:"introductory-chapter-earthworms-the-ecological-engineers-of-soil",totalDownloads:1059,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:null,signatures:"Sajal Ray",downloadPdfUrl:"/chapter/pdf-download/61487",previewPdfUrl:"/chapter/pdf-preview/61487",authors:[{id:"173697",title:"Prof.",name:"Sajal",surname:"Ray",slug:"sajal-ray",fullName:"Sajal Ray"}],corrections:null},{id:"61055",title:"Abundance and Diversity of Earthworms in Managed and Non- Managed Fallow Lands of Calakmul Reserve of Campeche, Mexico",doi:"10.5772/intechopen.75619",slug:"abundance-and-diversity-of-earthworms-in-managed-and-non-managed-fallow-lands-of-calakmul-reserve-of",totalDownloads:857,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In Mexico, the best preserved tropical rain forest is found in Calakmul Reserve, where fallow land management has been established. Fallow lands are developed as a consequence of a successional vegetation process after clearing the primary vegetation and milpa production. Forty-nine sites were studied, where 17 were managed fallow lands, 24 non-managed fallow lands, and 8 tropical rain forests. Earthworms were collected at the end of the raining season, and four monoliths of 25 × 25 × 30 cm were developed per site according to the TSBF method. We observed how Zapatadrilus siboney, a native species was dominant in managed and non-managed fallow lands. Earthworm’s total biomass and density were not significantly different between the managed and non-managed fallow lands. Earthworm’s species richness was significantly low in non-managed fallow lands. We observed a strong correlation between earthworm density and richness with the age of the fallow lands (r2: 0.9 and 0.7; p < 0.05, respectively). The management type of the fallow land seems to affect earthworm biomasses (r2: 0.56; p < 0.05).",signatures:"Esperanza Huerta Lwanga, Lucero Sánchez-del Cid, Ligia Esparza-\nOlguín, Eduardo Martinez-Romero, Ben de Jong and Susana\nOchoa-Gaona",downloadPdfUrl:"/chapter/pdf-download/61055",previewPdfUrl:"/chapter/pdf-preview/61055",authors:[{id:"229081",title:"Dr.",name:"Esperanza",surname:"Huerta Lwanga",slug:"esperanza-huerta-lwanga",fullName:"Esperanza Huerta Lwanga"}],corrections:null},{id:"59413",title:"Earthworms and Nematodes: The Ecological and Functional Interactions",doi:"10.5772/intechopen.74211",slug:"earthworms-and-nematodes-the-ecological-and-functional-interactions",totalDownloads:1516,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:1,abstract:"Soil invertebrate organisms are responsible for several biochemical processes indispensable for the correct functioning of ecosystems. Because of the high diversity of animals that occurs in the soil environment, some invertebrates such as earthworms and nematodes are highly important in trophic chains, with high number of species and the effect that they exert on both natural and agricultural systems. However, although numerous studies have evaluated the implications of these organisms in soil processes and their consequences on crop productivity, the interaction between earthworms and nematodes has received little attention in recent years. This chapter reviews studies focusing on the elucidation of the interaction between earthworms and nematodes in diverse situations in which they occur, for example, the vermicompost process and the native and agricultural systems. Several studies have shown that the direct and/or indirect action of earthworms can highly modify nematode populations. In addition, in the presence of earthworms, the damage caused by phytonematodes can be reduced in some crops.",signatures:"Jair Alves Dionísio, Wilian Carlo Demetrio and Arlei Maceda",downloadPdfUrl:"/chapter/pdf-download/59413",previewPdfUrl:"/chapter/pdf-preview/59413",authors:[{id:"225679",title:"Dr.",name:"Jair",surname:"Dionisio",slug:"jair-dionisio",fullName:"Jair Dionisio"},{id:"225686",title:"MSc.",name:"Arlei",surname:"Maceda",slug:"arlei-maceda",fullName:"Arlei Maceda"},{id:"225688",title:"Dr.",name:"Wilian",surname:"Demetrio",slug:"wilian-demetrio",fullName:"Wilian Demetrio"}],corrections:null},{id:"61906",title:"Exploration of Earthworms of India through Online Digital Library",doi:"10.5772/intechopen.75666",slug:"exploration-of-earthworms-of-india-through-online-digital-library",totalDownloads:1033,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:1,abstract:"Online digital library (http://earthwormsofindia.com) for identification of earthworms of India has been developed for the first time. The database comprises digital keys for identification of earthworms of India, diagnostics, and mathematical parameters to provide a useful supplement for traditional morphological taxonomists and nonexperts in this area. This will scientifically broaden the taxonomic coverage of Indian earthworms. The genomic signatures with short sequences from standardized regions of the genome for 1192 specimens of earthworms were generated. Earlier, species identification of adult earthworms was possible only by dissection of the anterior end. However, this method is labor intensive, time-consuming, and very difficult for nonspecialists, particularly when dealing with field collections consisting of several different earthworm species. Furthermore, identification is limited to adult worms, as most life stages are unidentifiable and many morphological and anatomical characteristics of earthworms are variable, consequently, and the degree of variability can differ and features can overlap the taxa. The present work appears pioneer endeavor in this direction, as there appears no work available on the digitization of earthworms of India.",signatures:"Samrendra Singh Thakur and Shweta Yadav",downloadPdfUrl:"/chapter/pdf-download/61906",previewPdfUrl:"/chapter/pdf-preview/61906",authors:[{id:"227681",title:"Dr.",name:"Shweta",surname:"Yadav",slug:"shweta-yadav",fullName:"Shweta Yadav"}],corrections:null},{id:"60445",title:"Earthworms and Vermicomposting",doi:"10.5772/intechopen.76088",slug:"earthworms-and-vermicomposting",totalDownloads:2436,totalCrossrefCites:10,totalDimensionsCites:14,hasAltmetrics:0,abstract:"Vermicomposting, the conversion of organic waste into vermicompost, is mediated by the combined action of earthworms and microorganisms. This interesting and attractive alternative to regular composting turns organic waste into a substrate that can be used as a soil amendment and as a growing medium for use in horticulture. Soil is not required in vermicomposting as the organic matter acts as both the substrate and food, and therefore only epigeic earthworms can be used in the process. Several earthworm species have been evaluated for their potential use in vermicomposting, including Eisenia fetida (Savigny), Eisenia andrei (Bouché), Dendrobaena veneta (Rosa), Dendrobaena hortensis (Michaelsen) Eudrilus eugeniae (Kinberg), and Perionyx excavatus (Perrier). The species most commonly used in vermicomposting and vermiculture facilities worldwide are Eisenia andrei and Eisenia fetida. This chapter reviews and updates the controversy surrounding the taxonomic differentiation between E. andrei and E. fetida, and between D. veneta and D. hortensis, showing that these are all different species and emphasizing the importance of maintaining pure cultures in vermicomposting systems. In the final section, methods of cultivating epigeic earthworms to ensure high rates of growth and reproduction are described.",signatures:"Jorge Domínguez",downloadPdfUrl:"/chapter/pdf-download/60445",previewPdfUrl:"/chapter/pdf-preview/60445",authors:[{id:"97521",title:"Dr.",name:"Jorge",surname:"Domínguez",slug:"jorge-dominguez",fullName:"Jorge Domínguez"}],corrections:null},{id:"60450",title:"Environmental Influence of Soil toward Effective Vermicomposting",doi:"10.5772/intechopen.75127",slug:"environmental-influence-of-soil-toward-effective-vermicomposting",totalDownloads:1958,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Vermicomposting is a process by which the organic waste is converted into manure with the help of earthworms. Growth rate, onset of maturity (clitellum development), rate of reproduction (cocoon production) and population buildup of earthworm during vermicomposting have been depend upon the conditions like temperature, moisture and physico-chemical properties of the feed mixtures. Eisenia fetida was superior to other epigeic species and tolerate wide range of temperature, moisture and pH. Endogeic species produced lesser cocoon than epigeic species and cocoon production decreased at low temperature. Maintenance of temperature and moisture content is the critical step for vermicomposting. Growth and maturation of earthworms was best at 20–25°C temperature with 80–85% moisture content. Increase temperature upto 30°C accelerated growth rate of earthworms and lessened the time to sexual maturity. Earthworms can survive in the soil contaminated with heavy metals by accumulating heavy metals in their tissues.",signatures:"Jaswinder Singh, Sharanpreet Singh, Adarsh Pal Vig and Arvinder\nKaur",downloadPdfUrl:"/chapter/pdf-download/60450",previewPdfUrl:"/chapter/pdf-preview/60450",authors:[{id:"229104",title:"Dr.",name:"Jaswinder",surname:"Singh",slug:"jaswinder-singh",fullName:"Jaswinder Singh"},{id:"240576",title:"Dr.",name:"Adarsh",surname:"Vig",slug:"adarsh-vig",fullName:"Adarsh Vig"},{id:"240577",title:"Dr.",name:"Arvinder",surname:"Kaur",slug:"arvinder-kaur",fullName:"Arvinder Kaur"},{id:"240578",title:"Mr.",name:"Sharanpreet",surname:"Singh",slug:"sharanpreet-singh",fullName:"Sharanpreet Singh"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"5899",title:"Organismal and Molecular Malacology",subtitle:null,isOpenForSubmission:!1,hash:"a7f042a23fd6991a546812db126ef875",slug:"organismal-and-molecular-malacology",bookSignature:"Sajal Ray",coverURL:"https://cdn.intechopen.com/books/images_new/5899.jpg",editedByType:"Edited by",editors:[{id:"173697",title:"Prof.",name:"Sajal",surname:"Ray",slug:"sajal-ray",fullName:"Sajal Ray"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6344",title:"Biological Resources of Water",subtitle:null,isOpenForSubmission:!1,hash:"ca4f407275697c7cf547debc6b1e85a9",slug:"biological-resources-of-water",bookSignature:"Sajal Ray",coverURL:"https://cdn.intechopen.com/books/images_new/6344.jpg",editedByType:"Edited by",editors:[{id:"173697",title:"Prof.",name:"Sajal",surname:"Ray",slug:"sajal-ray",fullName:"Sajal Ray"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"8421",title:"Invertebrates",subtitle:"Ecophysiology and Management",isOpenForSubmission:!1,hash:"524faf733c0ebf32b356f89b2148e6de",slug:"invertebrates-ecophysiology-and-management",bookSignature:"Sajal Ray, Genaro Diarte-Plata and Ruth Escamilla-Montes",coverURL:"https://cdn.intechopen.com/books/images_new/8421.jpg",editedByType:"Edited by",editors:[{id:"173697",title:"Prof.",name:"Sajal",surname:"Ray",slug:"sajal-ray",fullName:"Sajal Ray"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6883",title:"Cell Signalling",subtitle:"Thermodynamics and Molecular Control",isOpenForSubmission:!1,hash:"e4e17d85c0643c7f4d274fa9adbcc628",slug:"cell-signalling-thermodynamics-and-molecular-control",bookSignature:"Sajal Ray",coverURL:"https://cdn.intechopen.com/books/images_new/6883.jpg",editedByType:"Edited by",editors:[{id:"173697",title:"Prof.",name:"Sajal",surname:"Ray",slug:"sajal-ray",fullName:"Sajal Ray"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10738",title:"Update on Malacology",subtitle:null,isOpenForSubmission:!1,hash:"2a84e581549b3720e44e989c3c0be467",slug:"update-on-malacology",bookSignature:"Sajal Ray and Soumalya Mukherjee",coverURL:"https://cdn.intechopen.com/books/images_new/10738.jpg",editedByType:"Edited by",editors:[{id:"173697",title:"Prof.",name:"Sajal",surname:"Ray",slug:"sajal-ray",fullName:"Sajal Ray"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1398",title:"Principles, Application and Assessment in Soil Science",subtitle:null,isOpenForSubmission:!1,hash:"70c304305ba2727cc51774a1bc517e18",slug:"principles-application-and-assessment-in-soil-science",bookSignature:"E. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],ofsBooks:[]},correction:{item:{id:"66303",slug:"corrigendum-to-rural-landscape-architecture-traditional-versus-modern-fa-ade-designs-in-western-spai",title:"Corrigendum to: Rural Landscape Architecture: Traditional versus Modern Façade Designs in Western Spain",doi:null,correctionPDFUrl:"https://cdn.intechopen.com/pdfs/66303.pdf",downloadPdfUrl:"/chapter/pdf-download/66303",previewPdfUrl:"/chapter/pdf-preview/66303",totalDownloads:null,totalCrossrefCites:null,bibtexUrl:"/chapter/bibtex/66303",risUrl:"/chapter/ris/66303",chapter:{id:"57545",slug:"rural-landscape-architecture-traditional-versus-modern-fa-ade-designs-in-western-spain",signatures:"María Jesús Montero-Parejo, Jin Su Jeong, Julio Hernández-Blanco\nand Lorenzo García-Moruno",dateSubmitted:"September 6th 2017",dateReviewed:"October 11th 2017",datePrePublished:"December 20th 2017",datePublished:"September 19th 2018",book:{id:"6066",title:"Landscape Architecture",subtitle:"The Sense of Places, Models and Applications",fullTitle:"Landscape Architecture - The Sense of Places, Models and Applications",slug:"landscape-architecture-the-sense-of-places-models-and-applications",publishedDate:"September 19th 2018",bookSignature:"Amjad Almusaed",coverURL:"https://cdn.intechopen.com/books/images_new/6066.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"110471",title:"Prof.",name:"Amjad",middleName:"Zaki",surname:"Almusaed",slug:"amjad-almusaed",fullName:"Amjad Almusaed"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"221245",title:"Dr.",name:"María Jesús",middleName:null,surname:"Montero-Parejo",fullName:"María Jesús Montero-Parejo",slug:"maria-jesus-montero-parejo",email:"cmontero@unex.es",position:null,institution:null},{id:"223556",title:"Dr.",name:"Jin Su",middleName:null,surname:"Jeong",fullName:"Jin Su Jeong",slug:"jin-su-jeong",email:"jsbliss@gmail.com",position:null,institution:null},{id:"223557",title:"Prof.",name:"Julio",middleName:null,surname:"Hernández-Blanco",fullName:"Julio Hernández-Blanco",slug:"julio-hernandez-blanco",email:"juliohb@unex.es",position:null,institution:null},{id:"223558",title:"Prof.",name:"Lorenzo",middleName:null,surname:"García-Moruno",fullName:"Lorenzo García-Moruno",slug:"lorenzo-garcia-moruno",email:"lgmoruno@unex.es",position:null,institution:null}]}},chapter:{id:"57545",slug:"rural-landscape-architecture-traditional-versus-modern-fa-ade-designs-in-western-spain",signatures:"María Jesús Montero-Parejo, Jin Su Jeong, Julio Hernández-Blanco\nand Lorenzo García-Moruno",dateSubmitted:"September 6th 2017",dateReviewed:"October 11th 2017",datePrePublished:"December 20th 2017",datePublished:"September 19th 2018",book:{id:"6066",title:"Landscape Architecture",subtitle:"The Sense of Places, Models and Applications",fullTitle:"Landscape Architecture - The Sense of Places, Models and Applications",slug:"landscape-architecture-the-sense-of-places-models-and-applications",publishedDate:"September 19th 2018",bookSignature:"Amjad Almusaed",coverURL:"https://cdn.intechopen.com/books/images_new/6066.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"110471",title:"Prof.",name:"Amjad",middleName:"Zaki",surname:"Almusaed",slug:"amjad-almusaed",fullName:"Amjad Almusaed"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"221245",title:"Dr.",name:"María Jesús",middleName:null,surname:"Montero-Parejo",fullName:"María Jesús Montero-Parejo",slug:"maria-jesus-montero-parejo",email:"cmontero@unex.es",position:null,institution:null},{id:"223556",title:"Dr.",name:"Jin Su",middleName:null,surname:"Jeong",fullName:"Jin Su Jeong",slug:"jin-su-jeong",email:"jsbliss@gmail.com",position:null,institution:null},{id:"223557",title:"Prof.",name:"Julio",middleName:null,surname:"Hernández-Blanco",fullName:"Julio Hernández-Blanco",slug:"julio-hernandez-blanco",email:"juliohb@unex.es",position:null,institution:null},{id:"223558",title:"Prof.",name:"Lorenzo",middleName:null,surname:"García-Moruno",fullName:"Lorenzo García-Moruno",slug:"lorenzo-garcia-moruno",email:"lgmoruno@unex.es",position:null,institution:null}]},book:{id:"6066",title:"Landscape Architecture",subtitle:"The Sense of Places, Models and Applications",fullTitle:"Landscape Architecture - 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\r\n\tThe objective of this book is to make the food professionals acquainted with recent directions of the research work in food science. The different sections of this book project will describe the utilization of digital transformation in the food industry using the available applications of digital tools such as the internet of things (IoT), artificial intelligence (AI), sensor technologies, and blockchain. The effect of climate changes on the agro-industry will be discussed through the issues of climate changes, climate adaptation, agro-ecosystems, and environmental aspects and impacts. Recently, the food industry is subjected to unexpected new risks such as pandemics, lack of specific food supply, financial situations, and information technology problems so this too should be taken into consideration in the food science research work. As the food industry is a consumer-driven industry the continual improvement is a cornerstone in this industry. Recent technologies such as nanotechnology, membrane technology, and high-pressure technology besides the advanced analytical methods such as applications of the electron microscope and PCR would be covered.
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Taylor at the Midvale Steel Company in the 1880s as he progressed from machinist, to time clerk, to machine shop foreman, ultimately becoming chief engineer upon receiving a mechanical engineering degree in 1883. His participation in the American Society of Mechanical Engineers (ASME) provided him with the opportunity to present his shop management practices which were referred to as “work measurement” when applied to a specific work task (manual labor such as shoveling; skilled labor such as lathe operation). Broader applications to groups of workers in a plant or service organization (educational organizations, government agencies, the ASME) became known world-wide as Scientific Management [1], especially after Taylor testified before the US Interstate Commerce Commission in 1911.
Henry L. Gantt was recruited to perform work measurement at Midvale Steel under Taylor’s guidance, and as a consultant one speed and feed problems in metal cutting at Bethlehem Steel. Gantt modified one of Taylor’s published practices (piece-rate system) to account for productivity factors outside the workers control. Gantt became an independent consultant and ultimately lectured on IE at four US universities. Another early practitioner of IE was Morris L. Cooke, whom Taylor funded to work on efficiency and effectiveness of the ASME, the Carnegie Foundation, and the municipal government of Philadelphia. Frank B. Gilbreth originated the practice of work measurement in the construction trades, though he never attended college. His approach came to be known as time and motion study, which he first applied to bricklaying (a trade he learned as an apprentice). He insisted on division of labor between the brick mason (skilled labor) and the unskilled workers who “set up” the mason with bricks and fresh mortar; the specific location of the bricks and mortar relative to the mason, and even the consistency of the mortar, could be planned to make the mason as productive as possible. Furthermore, with appropriate design of the motions the mason should use, he demonstrated that the mason could increase the number of bricks laid in a given time by a factor of three. At age 27, Gilbreth founded (1895) a highly successful construction firm wherein all work was designed using time and motion study, but gave it up at age 44 to become a full-time management consultant. Frank’s wife, Lillian M. Gilbreth, was a PhD psychologist who assisted Frank in the preparation of six books between 1908 and 1917 to disseminate what he had learned about the broad topic of performance measurement, starting with the worker and broadening to the work processes and the overall work system.
As Japan began to recover from destruction of its industrial base during WWII, and to transition from essentially an agrarian society to an economic powerhouse, their industrial/production engineers originated many practices now considered part of modern industrial engineering. Starting in the 1970s and intensifying in the 1980s, there was significant debate in the US and other advanced economies in the West concerning what was enabling the Japanese to capture larger and larger market share in technological products such as automobiles, televisions, and copy machines. There was a US IE professor, Richard J. Schonberger, who spend a significant amount of time in Japan and authored several books [2, 3, 4] detailing his interviews and observations from visiting top-performing Japanese manufacturing firms. In
Fewer suppliers
Reduced part counts
Focused factories (focus on a narrow line of products)
Scheduling to a rate, instead of scheduling by lots
Fewer racks on the plant floor
More frequent deliveries (in-plant moves, as well as deliveries from suppliers)
Smaller plants
Shorter distances, less reporting, less inspectors, less buffer stock
Fewer job classifications.
In
Most US industrial engineers first learned details of TPM through the 1988 English version of Nakajima’s
OEE for a given machine, line, or plant is the product of availability, performance efficiency (processing rate ratioed with the design “ideal”), and quality rate (proportion of good products produced—the yield). Because each of these inputs is measured as a percentage, the closer OEE is to 100%, the better; world-class OEE is considered 85% or higher (some authors say 90% or higher). OEE is formally calculated using the following expressions, each expressed as a percentage:
The calculation of each of these quantities is illustrated by example in the references by Nakajima [5], and Robinson and Ginder [6]. The example in Nakajima further illustrates why the three input quantities to OEE are seldom calculated to be 100%. Essentially, the use of OEE in TPM uncovers the “Six Big Losses” which become the focus of improvement efforts by an individual engineer, or a team. The Six Big Losses are grouped as follows:
Losses that determine equipment availability
Equipment failure losses (requiring corrective maintenance)
Set-up and adjustment losses
Losses that determine performance efficiency
Idling and minor stoppages (e.g., clearing a jammed workpiece, or stopping for a visitor)
Reduced speed (e.g., running slower to avoid overheating, or avoid early job completion)
Losses that determine rate of quality products
Defects and rework
Reduced yield due to start-up losses (either due to nature of process, or company policy)
Some examples of how to improve OEE above status quo, based on the six big losses as numbered above, would be:
Study equipment failure and repair records. Use the Pareto Principle to identify which machines are causing downtime, in rank order: then, for the least available machine, identify the machine elements that are the causes of downtime, in rank order. Focus improvement efforts on the most problematic machines, and once identified, the most problematic machine elements.
To reduce set-up time, there is a Japanese practice originally known as Single Minute Change of Die (SMED)—meaning work to reduce change-over times to less than 10 minutes (single digits) with a goal of single minute change-overs; in the US, this practice is called Quick Changeover Technology and, for example, has been observed in casting machines in pipe shops, and welding machines for tubular steel products. This practice is essentially a specialized time and motion study, again carried out by a single engineer or improvement team, and the saving from avoided set-up losses can be substantial.
Periods of idling and instances of minor stoppages should be recorded (total time lost, situation and/or causes).
Reduced speed losses—there may be good reasons for running equipment at less than ideal processing rate, such as to avoid overstressing the equipment or safety concerns for the operator or other workers in the vicinity. In instances where work crews intentionally slow down, management needs to re-plan schedules so every worker can get in a full shift, having come to work intending to be paid for a full shift.
Defects and rework must be recorded and carefully examined to determine root causes, and then immediate corrective actions taken (standards modified or adjusted) to hopefully prevent the same problems in the future. Follow-up is critical by the engineer, manager, or team to verify the action installed is working and has become the standard.
Start-up losses may be unavoidable with the materials, machine, and set-up required; or, they may indicate a company policy that is outdated (current machine
For more details on data collection and the calculation/application of OEE, see three references focused specifically on OEE: Muchiri and Pintelon’s 2008 article “Literature Review and Practical Application Discussion” [11]; Hansen’s
A simple definition of service is “work performed for someone else.” In other words, services are all those economic activities in which the primary output is neither a good nor a construct, so services are for the most part intangible. Of course, services may occur
The Service Sector of the US economy in 2019 accounted for 79% of US employment. The percentage of service workers in other advanced economies are approximately 75% in Great Britain, 65% in France, and 60% in Germany and Japan. Service is considered a tertiary sector following the Primary Sector “Extractive” industries (Fishing, Agriculture, Mining, Oil and Gas, etc.) and the Secondary Sector “Transformative” industries (Manufacturing and Construction). The service sector is highly diverse; see the following groupings used by the US Dept. of Labor:
Trade, Transportation, and Utilities
Wholesale Trade (NAICS 42)
Retail Trade (NAICS 44-45)
Transportation and Warehousing (NAICS 48-49)
Utilities (NAICS 22)
Information (NAICS 51)
Financial Activities
Finance and Insurance (NAICS 52)
Real Estate and Rental and Leasing (NAICS 53)
Professional and Business Services
Professional Scientific and Technical Services (NAICS 54)
Management of Companies and Enterprises (NAICS 55)
Administrative and Support; Waste Management and Remediation (NAICS 56)
Education and Health Services
Educational Services (NAICS 61)
Health Care and Social Assistance (NAICS 62)
Leisure and Hospitality
Arts, Entertainment, and Recreation (NAICS 71)
Accommodations and Food Services (NAICS 72)
Other Services (except Public Administration) (NAICS 81)
Government
Characteristics of services are:
The product is intangible, for the most part
Usually performed in real time, with the customer present and often participating
Seldom inventoried, so must be delivered on the customer’s schedule
Something of value is provided (like manufacturing) but in a more immediate, personalized manner.
Quality of a product (service, good, or software) has been defined by Juran [17] as “fitness for use, in the intended environment” and by Deming [18] as “meets or exceeds customer expectations.” Therefore, a broad definition of service quality might be “fitness for use as determined by those features of the service that the customer considers to be beneficial.” As explained in Jain and Gupta [19], “services require a distinct framework for quality explication and measurement” and “involves evaluation of the outcome (i.e., what the customer actually receives from the service) and the process of service act (i.e., the manner in which the service is delivered).” Another line of research at that time concerned measurement of service expectations, pre- and post-consumption [20]. Parasuraman et al. [21] created the SERVQUAL scales and questionnaire organized around these five measures of service quality:
Reliability—the ability to perform the desired service dependably and accurately
Assurance—the knowledge and courtesy of employees and their ability to convey trust and confidence
Tangibles—the appearance of physical facilities, equipment, personnel, and communication materials
Empathy—the provision of caring, individualized attention to the customer
Responsiveness—the willingness to help customers and provide prompt service.
In a later publication [22], these same three authors presented a list of nine dimensions classifying how customers perceive service quality:
Tangibles—physical appearance
Reliability—performed as promised, consistently
Responsiveness
Competence
Credibility
Security/Safety
Access—easy to do business with
Communication—keeping customer informed
Understanding customer needs.
Pitt et al. [23] concluded that SERVQUAL is an appropriate instrument for researchers seeking a measure of information system service quality.
We have collected together six widely-known customer reactions to service quality:
Poor or inattentive service costs companies about 10% of volume annually (until corrected)
96% of unhappy customers never complain, but 90% never return. Each unhappy customer tells at least nine others.
Each happy customer tells five others, who may become future customers.
The best opportunity to increase sales and market share is through your present customer base
Customer perception of quality of service depends heavily on employee’s job satisfaction (dis-satisfaction)
Service personnel are
Let us consider several examples of the last point, which is very important for the industrial engineer:
A college instructor depends on:
The student registration system to provide accurate class rolls and a means to report final grades to the registrar
The classroom assignment system to provide a lecture hall to match the enrollment
The textbook ordering system to order, receive, and distribute the correct class materials in the correct quantities, on time
The classroom audio-visual system and computer software/internet access provided in the lecture hall.
A medical doctor seeing patients in his/her clinic depends on:
The patient appointment scheduling system
The measurement of patient vital signs by nurses as the visit begins, with computer access
Blood testing machines and/or radiological scans done prior to the visit, with computer access
Computer access to records of previous ailments and treatments, surgeries, vaccinations, etc.
Equipment he/she may use during the patient encounter.
A service representative at a cable television/internet provider depends on:
An information system showing the customer’s current service details, including start-up and service end dates
An information system showing additional or alternative services available to the customer based on location, with costs and time frame for change in service
A billing system should balances in accounts, due dates, penalties for late payments, etc.
A bank teller for customers who walk in the branch and queue for service, depends on:
An information system showing a customer’s accounts, safe deposit boxes, progress on any money electronically moved from or to customer’s accounts
An information system tracking cash transactions (deposits, dispersals, exchanges, etc.) completed by the teller and what should be the status of their cash drawer
In a large bank, a formal schedule of teller work assignments and for each, their schedule of breaks and lunch, and an out-of-office schedule for the current day and perhaps for the weeks or months ahead.
Overall Service Effectiveness (OSE) was first described in Berhan [24], and is the focus of the remainder of this chapter. The OSE metric for services extends the OEE production metric developed along with TPM as described earlier in the chapter. For the reader’s convenience, we shall demonstrate how OSE is a simple rewrite of the formulas for OEE and its three input components in a manner that fits service transactions an industrial engineer might be challenged to design or improve, using OSE as a guide.
In the equations below, the term “units” could be units of a manufactured good or quantities of a service completed. Examples of the latter might be: queries to an information systems; patients seen by a doctor or dentist; customer transactions at a bank—in person or electronic; riders transported by a bus or aircraft, or by the bus line or airline. Note these are all situations which an industrial engineer might encounter, and traditional IE tools such as queuing theory or system simulation might be in use. Agreeing with the OSE equations of Berhan [24], we shall use:
An example for an urban transportation system described in Berhan [24] adapted the equations for the three inputs above to the specifics of the service operation as follows:
Note that the bus service, like many encountered in modern society, is a “knowledge embedded service” [25] which are services which embed the customer value in a system that provides the service, so human-machine system reliability is a key component of the availability input to OSE for such services. Here, the driver’s knowledge of the route and how to operate the bus matters as much as the bus reliability.
Using real data from the public transport (bus) system in Addis Ababa, Ethiopia: Berhan first computed planned downtime (lunch breaks and shift changes), downtime and speed losses, performance efficiency losses, and finally quality and yield losses; Berhan then computed:
which yielded a system ‐ wide effectiveness measure of
showing this service system needs significant improvement in order to be rated “world-class”.
Just like in manufacturing, the OSE could also have been calculated for each bus individually, or for groups of busses that act together to cover a given route or sector within the city. Hence, OSE would be useful for service performance improvement at the bus, route, or (as demonstrated) system level.
This chapter provided background on the application of work measurement to services, starting with Taylor and his associates, and tracing the evolution from the plant performance metric Overall Equipment Effectiveness to an innovative service performance metric Overall Service Effectiveness (OSE). As illustrated in the analysis of an existing city bus system, the details used to compute the OSE inputs (availability, performance efficiency, quality rate) point toward actions that would improve OSE toward 100%. When designing a new service system (e.g., bus line, bank layout, fast food restaurant) the OSE metric can be used along with other industrial engineering tools (e.g., classic queuing formulas, systems simulation, engineering economy) to arrive at the most cost-effective layout, equipment/software, and staffing to handle forecast service demands.
Information Technology (IT) has already transformed into a business enabler and an intentional reason [1] in firms to date. However, the IT presence should get improved administration to cause more values [2] such as effective and efficient business processes, and profit growth [3]. Consequently, IT should replace from a business enabler to a business transformer as per IT ecosystem to convey the approach of IT services [4], in which IT does not only behave a driving instrument but also lets businesses innovate and disrupt customs to revitalize its presence inside the firm. In sequence, this revival will allow the firm to sustain its competitive advantage remains efficient [5].
Additionally, this chapter intends to verify the IT presence in terms of a business transformer in the firm operation [6, 7, 8] improving its performance. To do so, it needs a method to engineer the IT position in transforming the business. Also, the method is to show up the IT capitals bringing up more values. In other words, the method should involve a systems engineering viewpoint, which discloses prime thoughts of the systems approach such as holism, synthesis, interrelationships, along with the engineering-project-based estimates of system life cycle and requirements [9]. Likewise, the systems engineering utilizes an engineering design containing problem-solving, alternative solutions, solution selection, detailed model, model guard, and validated model [10].
Also, validating the chapter, the studies on the strength of resources on performance [11, 12, 13] turns into an essential theory to analyze IT systems as components of business completeness [14] because the studies emphasize on the resources an organization owns to promote its performance. This is in line with the intent of this chapter that also emphasizes that the business performance runs over IT resources owned [15, 16, 17]. Likewise, this chapter applies the Partial Adjustment Valuation (PAV) theory approach in congregating valuation methods among system components as promoted by [18, 19, 20]. Equally for the use of PAV in this chapter is the ability to relate between IT resources and the organizational performance mathematically. Thus, it is easier to trace the relationship of each component or subsystem for further synthesis.
Additionally, this chapter has continued the earlier studies addressing the IT value model from the ontological approach towards IT value engineering [21], the IT value model using a variance-based structural equation modeling (SEM) towards IT value engineering [22], engineering IT value in IT-based industries using PAV and RBV (Resource-Based View) approach [23], valuation methodology of IT value in the IT-based business [24], IT value engineering model and its optimum performance [25, 26], and hybrid configuration in IT value models [27]. The investigation leads IT to be valuable resources of the firm to revitalize the IT’s role through the IT value engineering model. Formerly, those studies had associated with a number of studies discussing the relationship between IT resources to business performance, such as [11, 12, 13, 17, 18, 19, 20, 28, 29]. Meanwhile, the IT value defined in this chapter is the added value in the form of a currency, which can also be expressed as the index ratio, generated due to the IT spending presence.
This chapter problem relates to past studies, which most of them had talked over the relationship between IT and the organization performance. Researchers identified the types of conclusion [8] about the relationship, where numerous conclusions show that the relationship might be positive [12, 13, 30], negative [3], and even neutral [11, 31], see Figure 1. Additionally, the positive relationship means that IT has a positive correlation to the organization to increase its business value and at that moment the negative is otherwise. The negative relationship shows in early empirical studies explaining the association between IT investment and organizational performance; they set off the controversy of the IT productivity paradox as Brynjolfsson’s (1993) conclusion [32].
The state of the art of ITVE.
In addition, the neutral relationship explicates that IT and business performance have no relationship in between as Strassman (1997) argued that there was no clear relationship between IT investment and a few measures of firm profitability, including return on asset, return on equity, and economic value added [11]. This chapter, further, addresses the positive relationship, although there are unfortunate situations where IT may have a negative impact as well [33].
The earlier studies, especially about the positive conclusion, have not yet talked about how to engineer the value of IT to deliver more benefits to the organization. On one hand, this issue is a complement study to the previous one because the chapter topic is a continual study of the past studies. On the other hand, also, this chapter may strengthen to close the past study, especially in terms of positive relationships between IT and the business performance, therefore, this chapter is to enrich and develop this domain further.
Additionally, the past studies seem like passive research, meaning that the work performed in the IT-equipped organization before. Consequently, the study has been simply conducted in conventional organizations and it has been less hard if it has maneuvered in a planned system. Therefore, the IT value engineering model chapter tries to offer a new approach to studying the role of IT within an organization. The approach initiates from RBV theory mentioning that the firm performance should root on the resources the firm owns, as the most famous fundamental theory in studying IT and organizational performance [13]. Then it explores sources of values of IT such that it can carry out a relationship formulation between IT value and the organization.
Figure 1 confirms to place this chapter among the others, which grounded on the earlier ones, nevertheless, with a different approach. For instance, from the subsystems point of views, this chapter solely resembles the Ravichandran’s model, which also took in four subsystems, namely IT resources, IS capabilities, IT support for core competencies, and firm performance [12]. Likewise, [34] exhausted four subsystems, although their nomenclature is different from Ravichandran’s. As for the other studies such as [11, 13] used three subsystems, namely IT resources, IT capability, and firm performance. However, [35] directly studied to link up between IT competency to firm performance, also [30, 36] simply studied between the data management capability to the performance as well as [18, 19, 20, 37, 38] researched the relationship between IT investment and public presentation. This chapter applies four subsystems based on RBV theory with their nomenclature as follows firm performance (FP), firm competence (FCC), firm capability (FC), and IT resource (ITR).
Furthermore, from an engineering point of views, the earlier studies generally exploited forward engineering, which begins from resources towards firm performance, while this chapter proposes reverse engineering for a serial configuration (see Figure 1), which begins from the required firm performance, afterwards, estimate the firm core competencies and firm capabilities to get IT resources composition. Also, from a methodological point of views, the earlier studies generally benefitted statistical approach or structural equation modeling (SEM) and RBV approach, excluding [18, 19, 20, 37, 38] who used PAV. This chapter appears with a different approach, whereas combining the earlier approaches such as RBV, PAV, and systems engineering at once. In other words, this chapter also carries the different final goal from the earlier ones, in which this chapter is to engineer IT resource about the required firm performance to let it performs at the lower cost.
Additionally, the chapter on the IT value was also conducted by the researchers such as [33] directing that the IT is an integrally part of a system of interrelated organizational factors, [39], who concentrated on the potential and realized IT values estimated by DEA (data envelopment analysis). Similarly, [6] estimated the IT business value by Cobb–Douglass function. Furthermore, [28, 40, 41] generally addressed the IT business value.
Meanwhile, to complete the chapter, the PAV [20] applies to correlate the subsystem input to its output. Additionally, the PAV usually operates with a static speed of adjustment or with a dynamic speed of adjustment in a researched object, on the contrary, in this chapter both the static and the dynamic speed of adjustment work together at a time in the PAV experiment. Likewise, thus far the PAV has applied in the country level study such as [18, 19, 20], however, this chapter tries to use the PAV at the firm level as the other study of the IT investment correlation to the firm productivity [8]. As for the chapter analysis, system engineering is to find this chapter because the IT value engineering essentially consists of subsystems such as electrical, computer, and value engineering. Likewise, the system engineering approach analyzes the chapter from both system engineering life cycle and model point of views.
In turn, the chapter result may turn away to become a framework to design an IT-based governing body by looking at several factors either internal or outside factors, including business environment ones. In other words, this chapter is an active chapter using its result, it can plan an organization as well as develop an established organization. Consequently, this chapter encompasses a broader domain of IT-based organization: established and planned systems.
Discussing a value means that it is addressing usefulness, worth, benefit. Furthermore, the value may disclose if there is an interaction between two or added systems or subsystems, in which one system works with the other one and vice versa, or the system works due to the other systems. Why would the systems mutually function? There is an energy that urges them to work, which is latterly called the value, usefulness, worth, benefit, competitive advantage, or other terms. In other words, this construction can facilitate accomplishing the stage of value creation by benefiting system processes.
There are various types of values such as normative value, realist value, and perceived value. Consecutively, the normative value relates to the required value as planned previously, the realist value pertains to the resulted value that comes from an accomplishment, and the perceived value is what consumer relatively perceives [16]. Additionally, if comprehended from cost management perspectives, the other types of values are the use value, meaning the value of the required function associated with the cost. Afterwards, the cost value, namely all cost values, dedicated to result in the item; the esteem value, means that the value of surplus cost to pay the additional items; the exchange value, namely the value of an item to exchange something else [42, 43].
Moreover, as a fundamental nature of the value definition of this research, the equation definition below bases further studies. This equation technically articulates a value (V) as an index resulted from a function (F) division by cost (C) as proposed by [44] as follows:
According to the formula, several efforts to bring the value gaining are:
For a similar function (F), diminish the cost (C) or
The cost (C) is stable, improve the function (F) or
The function (F) slightly reduced, the cost (C) significantly decreased or
The cost (C) a slight increase, the function (F) has increased significantly or
The function (F) increases while the cost (C) decreases.
It appears that by adjusting function and or cost, the system can control the value to ascend or descend consistent with what the purpose is, although, in practice, there are several considerations to essentially prepare in implementations [44].
As mentioned, the IT value may come from an estimate of the real worth, utility, or the IT system’s significance. This definition does not limit from what the worth, the utility, or the significance come from, thus, it does not prevent the multiple perspectives possibility. There is the stakeholder expectation such this, in turn, it influences the IT value achievement. In substance, value stems from the IT system to support the stakeholder aims attainment. For example, a debit card system that removes the requisite for cashiers to manually count cash may present cashiers with value since it lessens tension on their hands [45].
In addition, to explore the value of IT needs to investigate some scales reflecting these values. Accordingly, the metrics development is a necessity to measure IT values, however, there are certain criteria for the metric development as proposed by [45]. These criteria depart from selected questions that might be considered as follows:
What is the evidence to evaluate?
Where must valuation occur?
When must valuation occur?
How must valuations be interpreted?
It has been completely recognized that the IT value systems can manifest as a complex system consisting of various subsystems, components, subcomponents, and parts. Furthermore, as measuring the IT value, it is valuable to think about measurements that concentrate on. Definitely, the building of the metrics as a means to evaluate values results in a variety of problems, which necessitates doing so with care [45].
On the other point of view, the IT value study has to involve two sections: (i) IT variable, IT management variable or manifestation, and (ii) endogenous variable with IT economic impact [46]. Doing IT valuation involves complex issues, including social accomplishment so it requires over a period of time. Thus, this study should perform in an inclusive fashion such that the IT value research corresponds to an imperative flow of work that leads to business value. Likewise, there are economic associates of IT and its manifestations, and by itself, the scope of the research should restrict to examine the IT value to engineering it at the organizational level.
In the meantime, the IT resources that are subsequently delivering their capabilities can not create value for themselves within the organization. They need interaction with a business environment such that each will complement one another. As a result, IT infrastructures and organizational factors appear to work in a synergistic way, where these factors are part of the IT-based system consisting of IT human resources and IT management skills, rules, and policies. This is as the organizational system that comprises non-IT human resources and management skills, business procedures, information benefits, affiliation benefits, way of life, organization, and rules. In reality, IT is production machines, therefore, it generates value in the output configuration resulting in benefits due to business processing. In other forms, the value is apparent by itself in the form of process improvements such as saving time, process effectiveness, profitability, such as a higher return on assets, on investment, and consumer surplus such as higher customer satisfaction.
Furthermore, [34] stated that there are numerous factors in terms of the IT value creation chain that is essential and required conditions. Included in these conditions are the IS-strategy configuration, organizational restructuring, business process accomplishment, knowledge sharing, and IT management among others. Accordingly, those are critical in terms of the encouraging of the transformation process and renovation of the effectiveness of IT advantages. Additionally, there are four foremost subjects to demonstrate how IT value is shifting to describe, quantify and show it. The four subjects are (1) value IT-based co-creation, (2) IT embeddedness, (3) information approach, and (4) value extension.
The following stage of the IT value creation should concentrate on the co-creation of value by means of IT instead of IT value itself, further, it is called IT-based co-creation of value. While, the co-creation stands for the thought that (a) IT value cannot manifest in an isolated environment, it is progressively more being formed and accomplished due to actions of numerous parties, (b) value comes from strong joint associations among organizations, and (c) configurations and encouragements for the parties to contribute in and equitably assign emergent values are essential to keeping up co-creation. Moreover, IT embeddedness relates to the condition in which the IT is a central part of the process such that it turns into identical to the product. For example, the IT in a bank’s industry of instant credit check is intensely embedded in the loan endorsement process and hard to separate out. In other words, IT embeddedness is a fundamental model that attached to value co-creation, information mindset, and value expansion. Thus, it is plausible that preferred business capabilities drive IT embeddedness. Therefore, the effective convergence of preferred business capabilities and IT capabilities is a precondition “to realizing capabilities among organizations (co-creation), creating information value (information mindset), and ultimately realizing a wide repertoire of value (value expansion)” [34].
Tohidi (2011) stated that the idea of value engineering is to employ the projects, strengthen accomplishment and diminish costs in all life cycles of the projects. In this case, the lifetime value of the engineering project with the productivity increment can result in the value of the project, namely the output to the input ratio. Hence, the value engineering application is boiling down to performance improvement of inputs and outputs, by applying a theoretical approach of value engineering processes together with project management, project analysis, value analysis, and value management. Additionally, he mentioned that value engineering is constantly dealing with the growth of technology, reducing the unnecessary costs that do not relate to improving the products or services quality. Reducing costs in conventional point of views do not associate with creativity, it only refers to familiarities, feelings, and practices. On the contrary, in value engineering, the usage of knowledge, the problem recognition, the method of problem-solving, the development of the creative solutions could combine to develop comprehensive approaches [47].
Additionally, value engineering is a structured method to investigate the systems function and its completeness in dealing with a systems fundamental function accomplishment at the lowest cost. However, the functions of systems consistently keep up a better performance, trustworthiness, quality, and security [48]. Consequently, the value engineering process arrives at success if it is to discover opportunities to diminish needless costs and at the same time it is able to keep up and raise quality, consistency, accomplishment, and other customer needs on products or services. In terms of IT value, the IT generally boils down on the effectiveness and efficiency of processes, including achieving the best organizational performance. In other words, IT should disseminate value-added advantages through strategic alignment with the organizations.
Essentially, the IT presence within an organization is the norm for the era that is so, there is no one business organization that does not exploit the IT, where the simple difference is the amount of IT capacity. Empirically, such circumstances are something that is unquestionable, but the problem now is how to place the IT position within the business organization with the aim of its presence increasingly contribute enormous weights to the organization performance. Thus far, the IT inclusion in organizations is due to the demands of the times as technology-driven instead of market-driven, it is more emphasis on administrative rather than business development activities. Therefore, this chapter attempts to reposition IT as a means to improve competitive advantages of firms as indicated in Figure 2, which appears that IT should set it on the layer where is as the engineering processes culmination that preceded by electrical, computer, software, systems, and a complex system engineering to lead generating an IT value engineering.
IT value engineering position in an organizational environment.
Intrinsically, IT value engineering positions the IT at the more well-organized since it can go through an engineering process to create additional significant values as a continuation value generated on the preceding layers (see Figure 2). In other words, IT value engineering is the added value due to the engineering of the systems consisting of value, software, computer, electrical engineering. Meanwhile, the organizational environment is a circumstance where a firm should perform its business here, which are competitive forces including risks due to the business activities. The organizational environment should controllable to continue firm’s existence in business turbulence to sustain its competitive advantages, which are consisting of six categories, namely cost, differentiation, focus, execution, knowledge, and maneuverability advantages [5]. In this study, the competitive advantage that becomes a highlight is a cost-competitive advantage, which can result from the IT value engineering through a system optimization effort.
Furthermore, the IT value engineering has presented in an IT-based firm (see Figure 2), which is a firm that its core business has two wide-ranging groups of products and services, namely lifespan application development and support services and production processes [5] or industrial products and services that catch, transmit and display data and information by electronic means [49]. In the meantime, using RBV theory, this chapter departs from firm performance towards IT resources instead of the regular RBV, which originates from the resources to the firm performance in terms of the serial configuration.
This chapter proposes to structure the four subsystems of the RBV-based result, namely firm performance (FP), firm competence (FCC), firm capability (FC), and IT resource (ITR) to accomplish the rigorous IT value engineering concept by considering the nature of VRIN (valuable, rare, inimitable, non-substitutable) IT resources. In this case, each subsystem needs to identify its measures, which facilitate to determine the characteristics of the subsystem to build relationships with other subsystems or between the subsystem input and output [50]. Therefore, the FP typically addresses financial and efficiency performance, which manifests in, such as time-to-market and mass customization [51], profitability containing return on investment, return on asset, return on equity [16, 52]. While the FCC emphasizes to a firm’s core competence as the learning process ability to manage various resources and technology within the firm [53], consisting of three components: IT knowledge, IT operations, and IT objects. IT knowledge is the extent to which a firm possesses a body of technical knowledge about objects such as computer-based systems, while IT operations are the extent to which a firm utilizes IT to manage market and customer information. IT objects represent computer-based hardware, software, and support personnel [35].
Moreover, FC focuses on the assembling and installing IT-based resource capabilities to work together with the other resources in the firm [11] controlled by IT infrastructures, managed IT skills, and collaboration between IT and business [54]. The three measures combination can result in the firm capability, hence, it can create the VRIN IT resources, which also consist of IT infrastructure as tangible resources, human IT resources representing technical and managerial IT skills, and intangible IT-enabled resources such as knowledge assets, customer orientation, and synergy [11].
Preferably, to construct an IT spending model system, each measure or component of the subsystems relates one to another is not only qualitatively rational, but also quantitatively plausible as issued by [8]. However, to quantitatively plausible, the subsystems should also have complete measures that can manifest in a mathematical model. As proposed above, the mathematical formula to construct the relationship in this research is the partial adjustment valuation theory [20], which involves Cobb–Douglas production transformation as the input function.
Dedrick et al. (2003) stated that the failure of the subject area of the relationship between IT spending and the output performance at the firm level occurred due to the difficulty of quantifying measurement between these quantities [8]. Therefore, the chapter tries to do so by PAV. In this case, Nerlove (1958) was a developer of the origin of PAV theory and further developed by the researchers as it is today. The theory tells that the change in real output of a production process generally does not precisely fit the desired output alteration. The alteration measurement is in the present (t), compared with the previous period (t-1) for the real alteration and the desired alteration, which it is clear that there must be a coefficient bridging the relationship between the two alterations called a constant speed of adjustment [19, 20]. Therefore, if written in a mathematical formula, the theory manifests as follows:
It seems that yt is the real output of a production process unit, for example, a firm, in time t, as for yt-1 is the real output of the equal production process unit at time t – 1. While yt* is the desired output of the production process unit at time t, and μ is the coefficient depicting a constant speed of adjustment [20]. In an estimation process, an old-fashioned random error symbolized by ϵt needs to consider completing the formula. Consequently, Eq. (2) manifests as follows:
Whereas ϵt = conventional error. It appears that the real output is equal to the weighted average of the current desired output – with the weights μ – and the real output at a past time, with weights 1-μ. Furthermore, Lin and Kao (2014) suggested that μ in Eq. (2) and (3) can vary and be dynamic, therefore, μ may convert to μt where t represents fluctuations in time for the dynamic and μ for the constant or static. This scheme aims to provide more meaning of μ, for instance, the dynamic μ represents the speed of adjustment behavior in connecting the real output alteration with alterations in the desired one. In other words, these two alterations in output comprehend the dynamic nature of μ. Later, the scheme also exhibits the other signification of the state for further exploration [20].
At that time, the writing the equation above can turn to the subsequent Eqs. (4) and (5) [19, 20]:
Here f(Xt,β) is the alternate function of the desired output (yt*), which manifests in the form of a production function [8, 18, 19, 37, 38]. Accordingly, Xt could consist of a vector of production such as the regular capital (Kt), the regular labor expense (Lt), and the technology spending, in this study related to IT spending (It). For the benefit of variable estimation of the production function, it may consist of two compositions. The first is K, L, and I combination to accommodate the factors of capital, labor, and IT spending immediately, and the second is K and L combination that accommodates the factors of capital and labor. Thus, there are two models: Xt = (Kt, Lt, It) and Xt = (Kt, Lt) while β is the unknown parameters [19, 20].
Meanwhile, the function μt = g(St; γ) represents a dynamic speed of adjustment that accommodates variables, which fluctuate along with the different fluctuations of the required output such as return on equity (ROE). The magnitude of μt or μ is in the range of 0 and 1 [20], where the value of 0 means that the real output at time t is precisely equal to the real output of the previous period, t-1. While if 1 indicates that the real output is equivalent to the desired output. Conversely, μt is a St function, a vector of the variable, affecting the speed of adjustment of a firm, and γ is the unknown parameters. Therefore, to return to the original PAV theory, Eq. (4) is as follows:
Essentially the production function of the Eq. (4), namely f(Xt,β), can originate from various production functions such as the Cobb–Douglas (CD), the Box–Cox, the Box–Tidwell, the translog, and the constant elasticity of substitution functions [18, 19, 20, 37, 38]. The work may select all or a number of them as a test target. For that reason, this study just exploits the CD production function to substitute f(Xt,β) in Eq. (4). While, the CD equation is equally in the Eq. (7) below [18]:
The Eq. (7) presents the CD function with Xt consisting of production factors Kt, Lt, and It. Kt is the regular capital, Lt is the regular labor expense, and It is IT capital over time. In other words, Eq. (7) takes into account the IT capital inclusion. Meanwhile α, β1, β2, and β3 are the unknown parameters and vt ∼ N(0, σv2), and ut ∼ |N(0, σv2)|. In addition, to estimate these parameters performs in an estimation process. Equally for the CD function without It presence is as follows in Eq. (8):
Justification of the Eq. (8) is equivalent to the Eq. (7), apart just the It absence. While the Eq. (5), the speed of adjustment, can display as in Eq. (9) [20]:
Here μt is the dynamic speed of adjustment, and St is the dynamic factor that can manipulate the dynamics of μt suitable to the time-varying. Likewise, it may show as variances between the actual and the estimable variables of the firm. Furthermore, researchers provide a number of measures to fill these factors with various variables St, for example, return on equity, interest rate, firm size, growth option, economic value-added, and Tobin q [19, 20]. While γ1 and γ2 are the unknown parameters.
Moreover, if the Eqs. (7) and (9) substitute components of the Eq. (6), it produces an Eq. (10) as follows:
The Eq. (10) is for the three-factor production function, namely Kt, Lt, and It. It looks that the equation above is analogous to the Eq. (6), except that the production function, namely f (Xt, β), has converted to the Cobb–Douglas function [see Eq. (7)] and the speed of adjustment μt replaced by the Eq. (9). The variables and parameters justification of the equation is equivalent to the preceding equations, which substitute it. Meanwhile, for the two-factor function [Eqs. (7) and (8) substituted into the Eq. (6)], the equation becomes Eq. (11) as follows:
The equation justification is also analogous to the Eq. (10), except just the It absence. Furthermore, the Eqs. (10) and (11) are non-linear equations, their solution must also exploit a non-linear least square (NLS) application [20].
The first method of the ITVE is the meta-analysis approach, where the study concerns with the previous results in the analogous context, namely the relationship between IT resources and business performance. The method enriches the study since various validated hypotheses provide the researcher with strengthening the topic justification, therefore, the study can lead to conclude towards the objective of the chapter qualitatively [13]. In addition, this technique authorizes authors to study several papers addressing the IT value to the business performance relationship from the RBV point of view. Consequently, based on a number of the previous papers, particular topics such as IT resources, firm capabilities, firm core competencies and firm performance are categorically recognizable, where each group has to have relationship one to another for what this relationship leads to a means to link one category to another to construct a model of the IT value. Essentially, the resulting model is not only based on the meta-analysis approach, but also based on the RBV theory.
This method addresses PAV theory, which is linked components of each subsystem to investigate the correlation between IT resources and business performance. This section first reviews the PAV utilization in this chapter through the theory experimentally of the real facts to measure several IT-based firms using the PAV approach to examine the level of the IT value within each firm.
According to the meta-analysis, to create conceptual models, which involves logical and mathematical relationships, this method facilitates to develop two types of the model. The first model of IT value or the three-factor model is through substituting the Eq. (6) by the Eq. (7) and (9). Hence, the first model changes to the Eq. (10) above, which is the partial adjustment with Cobb–Douglas (CD) production function is inside and implying Kt (regular capital), Lt (labor expense), and It (IT spending) factors.
Meanwhile, through substituting the Eq. (6) by the Eq. (8) and (9) can create the second model of IT value (Kt and Lt) or the two-factor model as comprehended in the Eq. (11) above. Once again, both the Eqs. (10) and (11) are non-linear equations, thus, to estimate them must also use a non-linear least square (NLS) [20].
This study selects the return on equity (ROE) [20] as a component of the dynamic factor of the speed of adjustment since the ROE has an adjacent relationship to the regular capital (K), which is the firm equity, thus, the ROE can seem more representative as a dynamic factor (St) in this study than the others. Also, in order for the fluctuation rhythm of the K to compensate by the ROE fluctuation. While the ROE is a gain for the year of the parent firm divided by total equity of the parent firm at year-end December. Thus, the ROE becomes a dynamic factor (St, t is a period of time) of μt (the speed of adjustment) function to signify the dynamics of the speed of adjustment as comprehended in the Eq. (5) or (9). As for the static speed of adjustment, the Eq. (5) or (9) is equal to a constant, which is estimable in the non-linear least squares (NLS) estimation process. Moreover, the production function of the Eq. (4) devotes to the Cobb–Douglas (CD) function as explicated in the Eq. (7) and (8) above due to its simplicity and familiarity in production function transformations [18, 55].
For the purpose of assessment to separate the presence (with Iit) and the absence (without Iit) of the IT capital in the PAV approach, the estimate works on both Xit = (Kit, Lit, Iit) and Xit = (Kit, Lit). Here i = 1, …, r = 8, for example, for the number of testing firms, and t = 1,…, s = 11, for example, for the period of testing data, such as from 2004 to 2014. It is a time-varying, hence, the system is dynamic, therefore, for that reason, the study models can apply both Eqs. (10) and (11), however, caused the equations to overparameterize due to nonlinear, the estimate also needs the nonlinear least squares (NLS) application [20].
The Eqs. (10) and (11) estimation results in the unknown parameters, including γ1 and γ2 of the Eq. (9) for the dynamic speed of adjustment, while the static speed of adjustment is constant for all periods t. Therefore, the dynamic speed of adjustment as in the Eq. (9) is estimable to assess the dynamics of the μit. In addition, due to covering a period of time, the μit has the average speed of adjustment (ASA) as well. Assume γi estimate as
At this point, g(Sit;
In order to evaluate the change of the firm performance due to IT spending, Lin and Kao (2014) proposed the performance measures (PM) of the dynamic (μit) and static (μi) speeds of partial adjustment evaluate the performance change of the processing unit tested. This measurement manifests in Eq. (13) below [19, 20]:
To estimate the parameter γ and β, both parameters further designated to become
In this case, PVit is performance values of the processing unit or the firm. If averaged, the Eq. (14) results in:
Both the Eqs. (14) and (15) result in the currency value, however, that is further common, it would be superior if presented in the form of an index ratio. Consequently, PVit should be divided by the real output (yit), instead of a “devisor” (
The average value (APR) of Eq. (16) appears as using the subsequent formula:
Using this method, it is plausible to consider the amount of value between the IT capital presence and its absence within a capital expenditure of the firm. In other words, the IT value model using the PAV guides the study to comprehend the value of IT.
In order to evaluate the change in the firm performance due to IT spending, Lin and Kao (2014) proposed the performance measures (PM) of the dynamic (μit) and static (μi) speeds of partial adjustment to evaluate the performance change of the processing unit tested. This measurement manifests in Eq. (18) below [19, 20]:
To estimate the parameter γ and β, both parameters further designated to be
In this case, PVit is the performance values of the processing unit or the firm. If averaged, the Eq. (19) results in:
Both the Eqs. (19) and (20) result in the currency value, however, that is further common, it would be superior if presented in the form of an index ratio. Consequently, PVit should be divided by the real output (yit), instead of a “devisor” (
The average value (APR) of Eq. (21) is calculated using the subsequent formula:
Using this method, it is plausible to consider the amount of value between the IT capital presence and the absence of it within a capital expenditure of the firm. In other words, the IT value model using the PAV guides the study to comprehend the value of IT.
In essence, the applied method in this chapter is identical to the abovementioned method, namely starting from the structure of the conceptual model of IT value consisting of two types of models: three and two-factor models up until valuation of performance measures. However, the difference is simply on the goal, namely the earlier method aims to examine the PAV theory using the real facts to make sure that the IT inclusion in the business organization is material and valuable, while, this subchapter is to validate the resulted experiment data in several IT-based firms to certify that the PAV theory encounters the criteria of system measurements from a statistical point of views [8] to identify the level of the IT value of each firm. The validation is through model data examinations.
Here, the exploited data have been covering the period, for example, from 2004 to 2014, collected from the audited financial statements and the published annual reports. To compare between the presence (with It) and absence (without It) of the IT capital in the PAV approach [20], the estimation involves both Xt = (Kt, Lt, It), and Xt = (Kt, Lt) where t = 1…, 11 at the time of confirmed data from 2004 to 2014 for both static and dynamic speed of adjustment.
In reality, the adopted chapter method respects with the exposure of systems engineering processes offered by [50, 56], which is afterwards packaged in the method sequences as depicted below [10].
As mentioned, the primary problem of this chapter is how to carry out the need of worthy performance of the IT-based business organization to sustain competitive advantages by optimal costs, especially IT costs. Since this problem involves a variety of factors such as functional subsystems of RBV point of views, financial systems, competitive forces, business performance, risk management, resource management, and so forth. Accordingly, to solve this problem needs a systems engineering approach integrating various components into a unity solving the needed values.
In order to solve the problem, various alternative solutions could be a means to undo. Examples of the alternatives are with increasing the firm performance while the IT capital is constant, improving the IT competency and capability of the organization, and cost optimization by encouraging innovation, restructuring, IT cost-saving/ efficiency, and effective IT procurement. Indeed, each alternative has advantages and disadvantages, therefore, the preferred solution is all alternatives combinations to compile in a systems engineering process.
In the meantime, the preferred solution selected based on the five criteria that Kosky et al. (2013) initiated, namely “minimize information content, maintain the independence of functional requirements, ease of manufacture, robustness, and design for adjustability” [10].
According to [56], the systems engineering life cycle phases and the systems engineering method merges, which denotes that for each engineering phase of a horizontal nature, is vertically explored using these engineering models. This step is for concept development and engineering development phases, including each block of the phases. Meanwhile, the post-development phase is beyond this study. Consequently, the analytical results separated into two tables.
Furthermore, the information technology value engineering model exists to develop three types of models: parallel, serial, and hybrid ITVE. Likewise, their validation takes place to certify that the model is reasonable philosophically and technically.
The parallel model is in Figure 3 [25, 26]. This figure explicates that the principal subsystems of the model consist of firm performance (FP), firm core competence (FCC), firm capability (FC), and IT resource (ITR), which each subsystem links one to another in a parallel fashion. In a mathematical relationship, the parallel connection manifests an add operation (see Figure 3). It implies that the input (yt*) is proportionally divided into four sub-inputs, i.e. y*1t, y*2t, y*3t, and y*4t or yt* = y*1t + y*2t + y*3t + y*4t. Each subsystem has each speed of adjustment (μit, i = 1,2,3,4 and t = period), i.e. FP has μ1t, FCC has μ2t, FC has μ3t, and ITR has μ4t, whether static (constant) or dynamic [20]. Likewise, the output consists of four sub outputs, i.e. y1t, y2t, y3t, and y4t, which can appear as yt = y1t + y2t + y3t + y4t.
IT value engineering model in a parallel relationship [
Using the partial adjustment valuation approach [see the Eq. (3)], each subsystem could be mathematically revealed as follows [25, 26], see Figure 3:
Firm Performance (FP):
Firm Core Competence (FCC):
Firm Capability (FC):
Information Technology Resource (ITR):
If Eq. (24), Eq. (26), Eq. (28), and Eq. (30) are together added would result in Eq. (31) [25, 26]:
Where yt = the real output of period t, y1t = the real output of FP at period t, y*1t = the desired output (input) of FP, y1t-1 = the real output of the previous period (t-1), and μ1 = the constant speed of adjustment of FP. Similarly, y2t = the real output of FCC at period t, y*2t = the desired output (input) of FCC at period t, y2t-1 = the real output of the previous period (t-1), and μ2 = the constant speed of adjustment of FCC. Afterwards, y3t = the real output of FC at period t, y*3t = the desired output (input) of FC at period t, y3t-1 = the real output of the previous period (t-1), and μ3 = the constant speed of adjustment of FC. Finally, y4t = the real output of ITR at period t, y*4t = the desired output (input) of ITR period t, y4t-1 = the real output of the previous period (t-1), and μ4 = the constant speed of adjustment of ITR.
Instead of the parallel fashion, the serial ITVEM appears, in which to do so, suppose the Eq. (24), the Eq. (26), the Eq. (28), and the Eq. (30) exhibit in a serial relationship (see Figure 4), with an assumption that each output of a subsystem fully becomes an input of the subsequent ones, the end result is as Eq. (32) [25, 26].
IT value engineering model in a serial relationship [
As for the explanation of the symbols is equal to the parallel ITVE.
The hybrid configuration [27] is an option for structuring each subsystem in the chapter. Figure 5 explicates that the principal subsystems of the model consist of ITR, FC, FCC, and FP. It appears that the resources are the ITR consisting of the regular capital (Kt), the regular labor expense (Lt), and the technology spending, in this chapter related to IT spending (It). Furthermore, the resources become inputs of the FC subsystem as Kcap, Lcap, and Icap to be processed in resulting the FC output, viz. wmt (m = 1,2,3) or w1t, w2t, and w3t, see Figure 5. Likewise, the resources also become inputs of the FCC subsystem as Kcom, Lcom, and Icom to be processed in resulting the FC output, viz. vjt (j = 1,2,3) or v1t, v2t, and v3t, see Figure 5. Moreover, the output of both FC and FCC turn into the input of the FP. In other words, (w1t, w2t, w3t) and (v1t,v2t, v3t) appear as inputs of the FP.
IT value in the hybrid configuration [
Therefore, the PAV model of the hybrid configuration (see Figure 5) is as follows [27]:
Firm Capabilities “cap” (FC):
or
Where wmt = the real output of FC at period t, μm = the constant speed of adjustment of FC, αm = a constant of Cobb–Douglas function; β1, β2, and β3 are input elasticity of production factors regarding the regular capital (K), the labor expense (L), and the IT capital (I), and wmt-1 = the real output of the previous period (t-1). Hence, if the FC consists of three variables (m = 1, 2, and 3), viz. IT infrastructures, IT managerial skills, and Collaboration [54], thus each variable has output as follows [27].
IT infrastructures (w1t):
IT managerial skills (w2t):
Collaboration (w3t):
Firm Core Competence “com” (FCC):
or
Where vjt = the real output of FCC at period t, λj = the constant speed of adjustment of FCC, λj = a constant of Cobb–Douglas function; σ1,σ2, and σ3 are input elasticity of production factors regarding the regular capital (K), the labor expense (L), and the IT capital (I), and vjt-1 = the real output of the previous period (t-1). Hence, if the FCC consists of three variables (j = 1, 2, and 3), viz. IT knowledge, IT operations, and IT objects [35], thus each variable has output as follows [27].
IT knowledge (v1t):
IT managerial skills (v2t):
Collaboration (v3t):
Firm Performance “per” (FP):
or
Where znt = the real output of FP at period t, ηn = the constant speed of adjustment of FC, γn = a constant of Cobb–Douglas function; ϕ1 and ϕ2 are input elasticity of production factors regarding the FC output (w1t,w2t,w3t) and the FCC output (v1t,v2t,v3t), and znt-1 = the real output of the previous period (t-1). Hence, if the FP consists of three variables (n = 1, 2, and 3), viz. ROE, ROA, and Revenue [16], thus each variable has output as follows [27].
ROE (z1t):
ROA (z2t):
Revenue (z3t):
The ITVE optimization involves the cost minimization in accordance with the major problem of this research to raise the firm performance at optimal cost [26]. To do so, it needs several assumptions [57] along with the optimization process. For example, the Cobb–Douglas production function [20] replaces each the desired output (the starred y*it, i = 1, 2, 3, 4 and t = 1, …, 11, for example) of subsystems. The Cobb-Douglass function is as follows:
Whereas y*it = the desired output with i = subsystem and t = period, Kit = the regular capital, Lit = the labor expense, Iit = the IT capital, α = total factor productivity, and β1, β2, β3 = the output elasticity of the regular capital, the labor expense, and the IT capital. Therefore, the partial adjustment for each subsystem is as follows (to simplify, i is disappearing):
Whereas μt is the static speed of adjustment and yt-1 is the revenue in the earlier period. Additionally, for cost minimization, the partial derivatives of the Eq. (48) should fulfill these conditions [58, 59]:
If the Eq. (49) is mathematically derived to K, L, and I, it respectively results in the following equations (whereas p1, p2, and p3 are added to the equations as unit prices of the regular capital (K), the labor expense (L), and the IT capital (I):
Using the Eq. (50) prerequisites, the Eq. (51) = the Eq. (52) = the Eq. (53), further equations arise as follows:
If the Eq. (49) is substituted by the Eq. (54) such that the new equation appears in the regular capital (K) variable, the equation is as Eq. (55) and afterwards simplified to become Eq. (56).
Furthermore, the Eq. (56) becomes K variable as in Eq. (57) and afterwards simplified as in Eq. (58) as follows:
Using the equivalent way, the variable L and I can become as follows:
If K, L, and I are multiplying p1, p2, and p3 as unit prices respectively, then it appears as follows:
Moreover, the Eqs. (61), (62), and (63) substituted into Eq. (64), the total cost of yielding y units in the low-cost technique manifest as the Eq. (64) and (65).
Where B:
Whereas p1, p2, and p3 is unit prices of the regular capital (Kt), the labor expense (Lt), and the IT capital (It) respectively, yt is the real output of period t, yt-1 is the real output of earlier period t-1, and C is the total cost [26].
The significant problem surrounding this study is to sustain superior firm performance as desired at optimal costs due to the IT presence, which has inevitably become a need for running the business world. Numerous studies on the relationship of the firm performance of the IT resource were more focused on a statistical method that links between components using survey data. In essence, this study undertakes an analogous study, but with a different approach, namely, the systems engineering approach combined with RBV theory, systems engineering, the theory of partial adjustment, including the CD production function, which, in turn, lead to creating the ITVE. Furthermore, to create the ITVE, the followed stages are to build the conceptual model of the IT value based on the RBV theory, model experiment using PAV, validate PAV, model the ITVE, confirm the ITVE and study managerial impacts of the model.
The conceptual model of IT value has logically exemplified the relationship between ITR, FC, FCC, and FP in terms of competitive advantages. The theory of partial adjustment links logically the model, which formulates it in two types of models. Explicitly, the first model addresses PAV with the IT capital presence (with It) inside of its production function, and the second model with the IT capital absence (without It). The applied production function is the CD function while the dynamic factor component of the speed of adjustment is the ROE. However, it may be replaced by other dynamic factors.
The principal problem of this chapter is how to achieve the optimal resources, for instance, IT resource costs, for required business performance. By benefiting the earlier studies, namely the systems engineering methodology, the conceptual model of IT value, the RBV theory, and the PAV theory can solve this problem so that the solution results in the IT value engineering. Furthermore, using the analysis results, a synthesis work leads to composing a block diagram, which depicts a model in terms of the systems engineering of IT value engineering framework, which ultimately results in serial, parallel, and hybrid configurations. Likewise, by benefiting CD production function involved within PAV, the optimal cost of the required firm performance occurs. For that reason, it should surely be an experiment as a simulation on work mechanisms of the model. Consequently, the ITVE technically appears as a framework to study IT value models. However, in practice, this model contributes to managerial implications, which should reinforce the match between techniques and practices.
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. 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Bioremediation is an attractive and successful cleaning technique to remove toxic waste from polluted environment. Bioremediation is highly involved in degradation, eradication, immobilization, or detoxification diverse chemical wastes and physical hazardous materials from the surrounding through the all-inclusive and action of microorganisms. The main principle is degrading and converting pollutants to less toxic forms. Bioremediation can be carried out ex-situ and in-situ, depending on several factors, which include but not limited to cost, site characteristics, type, and concentration of pollutants. Hence, appropriate bioremediation technique is selected. Additionally, the major methodologies to develop bioremediation are biostimulation, bioaugmentation, bioventing, biopiles, and bioattenuation provided the environmental factors that decide the completion of bioremediation. Bioremediation is the most effective, economical, eco-friendly management tool to manage the polluted environment. All bioremediation techniques have its own advantage and disadvantage because it has its own specific applications.",book:{id:"9343",slug:"trace-metals-in-the-environment-new-approaches-and-recent-advances",title:"Trace Metals in the Environment",fullTitle:"Trace Metals in the Environment - New Approaches and Recent Advances"},signatures:"Indu Sharma",authors:[{id:"301262",title:"Associate Prof.",name:"Indu",middleName:null,surname:"Sharma",slug:"indu-sharma",fullName:"Indu Sharma"}]},{id:"60680",title:"Environmental Contamination by Heavy Metals",slug:"environmental-contamination-by-heavy-metals",totalDownloads:16e3,totalCrossrefCites:165,totalDimensionsCites:359,abstract:"The environment and its compartments have been severely polluted by heavy metals. This has compromised the ability of the environment to foster life and render its intrinsic values. Heavy metals are known to be naturally occurring compounds, but anthropogenic activities introduce them in large quantities in different environmental compartments. This leads to the environment’s ability to foster life being reduced as human, animal, and plant health become threatened. This occurs due to bioaccumulation in the food chains as a result of the nondegradable state of the heavy metals. Remediation of heavy metals requires special attention to protect soil quality, air quality, water quality, human health, animal health, and all spheres as a collection. Developed physical and chemical heavy metal remediation technologies are demanding costs which are not feasible, time-consuming, and release additional waste to the environment. This chapter summarises the problems related to heavy metal pollution and various remediation technologies. A case study in South Africa mines were also used.",book:{id:"6534",slug:"heavy-metals",title:"Heavy Metals",fullTitle:"Heavy Metals"},signatures:"Vhahangwele Masindi and Khathutshelo L. Muedi",authors:[{id:"225304",title:"Dr.",name:"Vhahangwele",middleName:null,surname:"Masindi",slug:"vhahangwele-masindi",fullName:"Vhahangwele Masindi"},{id:"241403",title:"M.Sc.",name:"Khathutshelo",middleName:"Lilith",surname:"Muedi",slug:"khathutshelo-muedi",fullName:"Khathutshelo Muedi"}]},{id:"59905",title:"Synthesis of Silver Nanoparticles",slug:"synthesis-of-silver-nanoparticles",totalDownloads:6761,totalCrossrefCites:9,totalDimensionsCites:18,abstract:"Nanoparticles of noble metals, especially the silver nanoparticles, have been widely used in different fields of science. Their unique properties, which can be incorporated into biosensor materials, composite fibers, cosmetic products, antimicrobial applications, conducting materials and electronic components, make them a very important subject to be studied by chemistry, biology, healthcare, electronic and other related branches. These unique properties depend upon size and shape of the silver nanoparticles. Different preparation methods have been reported for the synthesis of the silver nanoparticles, such as electron irradiation, laser ablation, chemical reduction, biological artificial methods, photochemical methods and microwave processing. 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The correlation between stability and reactivity of coordination compounds has been described in this chapter. This chapter also enlists the factors influencing the stability of metal complexes such as the nature of metal ions, ligands, bonding between metal ions and ligands, etc. In addition, the methods available for the determination of stability constants are given in detail.",book:{id:"9190",slug:"stability-and-applications-of-coordination-compounds",title:"Stability and Applications of Coordination Compounds",fullTitle:"Stability and Applications of Coordination Compounds"},signatures:"Senthilkumar Muthaiah, Anita Bhatia and Muthukumar Kannan",authors:null},{id:"60518",title:"Synthetic Methods for Titanium Dioxide Nanoparticles: A Review",slug:"synthetic-methods-for-titanium-dioxide-nanoparticles-a-review",totalDownloads:5149,totalCrossrefCites:26,totalDimensionsCites:50,abstract:"Titanium dioxide (TiO2) semiconductor nanoparticles are one kind of important and promising photocatalysts in photocatalysis because of their unique optical and electronic properties. Their properties, which are determined by the preparation method, are very crucial in photocatalysis. In this chapter, an overview was carried out on the different methods that are used or have been used to prepare titanium dioxide nanoparticles. There are various methods that can be used to synthesize TiO2 and the most commonly used methods include sol-gel process, chemical vapor deposition (CVD) and hydrothermal method among others. This review will focus on selected preparation methods of titanium dioxide photocatalyst.",book:{id:"6426",slug:"titanium-dioxide-material-for-a-sustainable-environment",title:"Titanium Dioxide",fullTitle:"Titanium Dioxide - Material for a Sustainable Environment"},signatures:"Pardon Nyamukamba, Omobola Okoh, Henry Mungondori,\nRaymond Taziwa and Simcelile Zinya",authors:[{id:"196100",title:"Dr.",name:"Raymond",middleName:null,surname:"Taziwa",slug:"raymond-taziwa",fullName:"Raymond Taziwa"},{id:"219920",title:"Prof.",name:"Omobola",middleName:null,surname:"Okoh",slug:"omobola-okoh",fullName:"Omobola Okoh"},{id:"226567",title:"Dr.",name:"Pardon",middleName:null,surname:"Nyamukamba",slug:"pardon-nyamukamba",fullName:"Pardon Nyamukamba"},{id:"239758",title:"Mr.",name:"Simcelile",middleName:null,surname:"Zinya",slug:"simcelile-zinya",fullName:"Simcelile Zinya"}]}],onlineFirstChaptersFilter:{topicId:"158",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:98,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:287,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:10,numberOfPublishedChapters:103,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:11,numberOfOpenTopics:4,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. 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He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). 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He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"13633",title:"Prof.",name:"Abdelhamid",middleName:null,surname:"Mellouk",slug:"abdelhamid-mellouk",fullName:"Abdelhamid Mellouk",profilePictureURL:"https://mts.intechopen.com/storage/users/13633/images/1567_n.jpg",institutionString:null,institution:{name:"Paris 12 Val de Marne 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