A Review on Technology Forecasting Methods PDF

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Seoul National University

Daekook Kang, Wooseok Jang, Hyeonjeong Lee, and Hyun Joung No

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technology forecasting technology industry TF trend technology trajectory

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This article reviews technology forecasting (TF) methods and their application areas. It profiles developments in TF research over time, examines the industries using various TF methods, and identifies their relationships. The study is based on international refereed journal articles from 1970 to 2013, using tools like Google Scholar, ScienceDirect, and others. Its findings cover various aspects, including the number of articles, leading journals, and frequently applied TF methods like Delphi, patent analysis, and technology roadmaps. The study emphasizes understanding developments in TF and application areas such as information technology, materials, and telecommunication services, among others.

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World Academy of Science, Engineering and Technology International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering Vol:7, No:4,...

World Academy of Science, Engineering and Technology International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering Vol:7, No:4, 2013 A Review on Technology Forecasting Methods and Their Application Area Daekook Kang, Wooseok Jang, Hyeonjeong Lee, and Hyun Joung No remains a popular technique for technology forecasting. More Abstract—Technology changes have been acknowledged as a advanced Delphi method also has been developed combining critical factor in determining competitiveness of organization. Under Bayesian weighting and Delphi questionnaire. Meanwhile, such environment, the right anticipation of technology change has recently, patent analysis frequently has been used as an been of huge importance in strategic planning. To monitor technology objective method to recognize the trends in technological change, technology forecasting (TF) is frequently utilized. In academic perspective, TF has received great attention for a long time. development [7-9]. International Science Index, Industrial and Manufacturing Engineering Vol:7, No:4, 2013 waset.org/Publication/2934 However, few researches have been conducted to provide overview of However, even though there are vast amounts of TF research, the TF literature. Even though some studies deals with review of TF till now, few attempts have been made to provide overview of research, they generally focused on type and characteristics of various the TF literature as shown in Table I. Table I shows that four TF TF, so hardly provides information about patterns of TF research and review articles [1, 3, 10, 11] have been published so far. These which TF method is used in certain technology industry. Accordingly, review articles have some limitations. First, three of them only this study profile developments in and patterns of scholarly research in TF over time. Also, this study investigates which technology focused on type and characteristics of various TF methods, industries have used certain TF method and identifies their while only one covered evolution and practical applications of relationships. This study will help in understanding TF research trend TF. Even though practical applications of TF were studied, it and their application area. hardly provided information about which TF method were used in certain technology industry. Second, these articles focused Keywords—Technology forecasting, technology industry, TF TF itself so didn’t cover patterns of scholarly research in TF trend, technology trajectory. over time. Third, these review articles included some TF research dealing with the demand forecasting of technology I. INTRODUCTION such as diffusion model and simple time series analysis. R ECENTLY, the globalization and technology changes has been recognized as two mutually reinforcing factors that are playing the focal role for competitiveness of organization However, this demand forecasting method for technology is not appropriate for exploring the trend of technological advancement and anticipating the potential direction of. Under such turbulent environment, the timely anticipation technology which are defined as the main purposes of TF in our and forecast of these challenges have been of vital importance study. Therefore, to provide accurate overview of the TF for incorporating technological changes into strategic planning literature, TF research containing this kind of methods is process. A good forecast of technology can help maximize excluded in this study. gain and minimize loss for the organization from a long-term Accordingly, the present study aims to contribute to the perspective. extant literature on TF in three ways: Technology forecasting (TF) has been acknowledged as an effective tool in order to anticipate and understand the potential TABLE I EXITING TF REVIEW RELATED ARTICLES direction, rate, and effects of technological change [3-5]. Given Article Main characteristic the effectiveness of TF, this area has received considerable Slocum and Lundberg (2001) Emphasis on TF method research attention during 40 years. For example, Delphi Mishra, Deshmukh, and Vrat (2002) Development of methodology to select appropriate technique for TF Martino (2003) Emphasis on TF method Daekook Kang is with the Department of Industrial Engineering, Seoul Firat, Madnick, and, Woon (2008) Summarization of various field of TF, National University, Daehak-dong, Gwanak-gu, Seoul, 151-744, Republic of its purposes, evolution, applications Korea (phone: 82-10-3171-0670; fax: 82-2-878-3511; e-mail: [email protected]). Wooseok Jang is with the Department of Industrial Engineering, Seoul 1. To profile developments in and patterns of scholarly National University, Daehak-dong, Gwanak-gu, Seoul, 151-744, Republic of research in TF over time Korea (phone: 82-10-2080-4921; fax: 82-2-878-3511; e-mail: [email protected]). 2. To investigate which technology industries have used Hyeonjeong Lee is with the Department of Industrial Engineering, Seoul certain TF method and identify their relationships National University, Daehak-dong, Gwanak-gu, Seoul, 151-744, Republic of 3. To provide suggestions for future research in TF Korea (phone: 82-10-3114-9115; fax: 82-2-878-3511; e-mail: [email protected]). Hyun Joung No is with School of Mechanical and Aerospace Engineering, The remainder of this paper is organized as follows. Section Seoul National University, Daehak-dong, Gwanak-gu, Seoul, 151-744, II describes the methodology used for the study. Then, in Republic of Korea (phone: 82-10-7148-1978; fax: 82-2-878-3511; e-mail: [email protected]). International Scholarly and Scientific Research & Innovation 7(4) 2013 591 scholar.waset.org/1999.8/2934 World Academy of Science, Engineering and Technology International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering Vol:7, No:4, 2013 seection III show ws trends in TF research. Finally, Secttion IV reggion. Foor these reasoons, this stud dy utilized trreemap cooncludes the paper p with conntributions andd future researrch. vissualization. II. METTHODOLOGY III. TREND IN TF RESEAR RCH As one of the main aims of o the presentt study was too profile A. Number off TF Articles aand their Distrribution over Time T deevelopments ini and patterns of scholarlyy research in TF T over tim me, internatioonal refereed journals were considered too be the m suitable publication most p forr examination n in this studyy. Thus, w chose to covver the whole pperiod from thhe year when the we t first TFF article appeaared in an acaddemic journall (1970) till thee end of 20013. This study used u a two-phaased research approach to provide p m meaningful impplications. Firrst, all publiccation articles on TF w were collected. Second, bassed on these articles, pattterns of sccholarly reseaarch in TF andd application areas of TF method International Science Index, Industrial and Manufacturing Engineering Vol:7, No:4, 2013 waset.org/Publication/2934 w investigatted. were Phase 1: Colllecting the Arrticles An extensivee search of the extant literaature related with w TF was conducted to develop a database w d of TF F articles. The articles w collected through were t follow wing sources: 1. Google Sch holar and Sciiencedirect. 2. NDSL andd RISS whicch are Korea websites prooviding Fig. 1 Number of TF related articles publish hed between 1970 and internationnal science innformation suuch as articlles and 2013 patent. Though TF reesearch dates bback 44 yearss, most of the articles a 3. Reference lists of TF rellated books, an nd TF review articles in journal have been publisheed in the last 10 1 years. Espeecially, Especially, as a first sttep, we searrched articless using in the last 5 yearrs, half of the aarticles have been b published d. Also, keeywords suchh as technologgy forecastingg, technologyy trend, intteresting findiing is that thee most recent years follow a clear annd technologyy trajectory. TThen, articles related with demand d uppward directionn as shown inn Fig. 1. foorecasting of technology t weere excluded. As a result, tootal 106 arrticles were coollected that were publisheed in a periodd of 44 B. Leading TF F Journals yeears (1970-2013). Phase 2: Invvestigating Treend in TF Research In phase 2, trrend in TF reseearch was investigated. Conncretely, foollowing fourr issues were investigated based on coollected arrticles. 1. Number off TF Articles aand their distriibution over tiime 2. Leading TF F Journals 3. TF methodds and their typpes 4. Applicationn areas of TF To investigaate these fourr trends in TF F research, we w used sppotfire which was a prograams providing data visualization, annalytic dashboards and appplications, and a forward-llooking prredictive analyysis with inteelligence. In this t study, baar chart, treeemap, and pie chart were w used to derive meaaningful innformation aboout trend in TF F research. Figg. 2 Treemap foor journal of TF F articles Especially, trreemap is info formation visuualization metthod for diisplaying hieraarchical (tree--structured) daata as a set off nested Fig. 2 showss treemap forr journal of TFT articles. Articles A reectangles. Eachh branch of the tree is givenn a rectangle, which w is rellated with TF F research havve been published in 63 diifferent thhen tiled withh smaller rectaangles represeenting sub-brranches. jouurnals. Only 8 journals pubblished almostt 50 % of the all TF Trreemap has tw wo advantagees for the dataa visualizationn. First, artticles, namelyy Technologicaal Forecastingg and Social Change C onne can often easily e see patteerns that woulld be difficultt to spot (266 articles), Expert E Systemss With Applications (6 arrticles), inn other ways, such s as if a ceertain color is particularly reelevant. Fooresight - Thee journal of FFuture Studies, Strategic Thhinking Seecond, treem map visualizattion make efficient e use of the annd Policy (4 articles), Inddustrial Mannagement and d Data avvailable displaay space, mappping hierarchiies onto a rectangular Sys ystems (4 articcles), Telecommmunications Policy (4 arrticles), ETTRI Journal (33 articles), R&&D Managem ment (3 articles), and International Scholarly and Scientific Research & Innovation 7(4) 2013 592 scholar.waset.org/1999.8/2934 World Academy of Science, Engineering and Technology International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering Vol:7, No:4, 2013 Teechnovation (3 3 articles). Th he other journaal published leess than boound methods for seeing whhere events an nd trends might take 3 articles. us from the present to the fuuture such as Delphi D metho ods and tecchnology road dmap. In con ntrast, normattive approach hes are C. TF Method ds and Their Types T inwward bound methods. m Thuus, they begin n with a prelimminary 1. Qualitativee and Quantitaative Approacches over Tim me vieew of a possib ble (often a ddesirable) futu ure. Then, theyy work baackwards to see if and how tthese might fu utures might orr might noot grow out off the present such as simu ulations and network tecchniques. Meaanwhile, subjeective approa aches are assessment meethods based on the individual subjectiive opinion such s as surrvey and interrview. In Fig. 4, mo ost frequently used method in TF researcch was expploratory app proaches such as Delphi, curve fitting g, data en nvelopment an nalysis, and ttechnology ro oadmap. Meaanwhile noormative appro oaches such as a patent analy ysis and TRIZ Z were useed in some deegree. However, subjective approaches such s as inddustry analysiis and intervieew were not ussed very much h. International Science Index, Industrial and Manufacturing Engineering Vol:7, No:4, 2013 waset.org/Publication/2934 D. Application n Areas of TF F 1. Applicatio on Areas (100 industries) and TF Meth hod (9 cattegories) F 3 Number of qualitative and Fig. a quantitativee approaches beetween 19700 and 2013 Fig. 3 depiccts the numbeer of qualitattive and quan ntitative ap pproaches betw ween 1970 annd 2013. Wheen the first TF F article ap ppeared in an academic jou urnal with qua alitative appro oach in 19970, many arrticles contain ning qualitatiive and quan ntitative appproaches haave been pub blished. Firstt TF researcch with quuantitative ap pproach was published p in 1980. This research r prroposed TF wiith logistic env velope approxximation meth hod. A After this reseaarch was pubblished, many quantitative studies haave been pu ublished com mpared with qualitative studies. s Esspecially, in last 5 years, quantitativee studies hav ve been puublished almoost twice as muuch as qualita ative studies. 2. Leading TF T Methods Fig. 5 Trreemap for appllication areas an nd TF method d application aarea of TF reseearch into 10 sectors We classified baased on Globall Industry Classsification Staandard (GICS)) which is an industry taaxonomy deveeloped by MS SCI and Stand dard & Pooor's (S&P). The T GICS strructure consists of 10 secto ors, 24 inddustry groups. In this studyy, we adopted sector classiffication schheme due to the ease of analysis. a Alsoo, to provide a clear vissualization an nd ease of inteerpretation, tyypes of TF methods m weere classified based on the classification scheme of prrevious ressearch suggessting 9 categgories of TF methods as expert oppinion, trend analysis, a monitoring and in ntelligence meethods, sta atistical meth hods, modeliing and sim mulation, scen narios, valuing/decision n/economics methods, m descriptive and matrices meethods, and crreativity. Fig. 4 Treem map for TF meth hods From Fig. 5, we can knoow that inforrmation techn nology, maaterials, and teelecommunicaation servicess have receiveed most By referringg previous reesearch sugg gesting classiffication ressearch attentio ons as application areas of TF T methods. Among A sccheme of TF F methods aas exploratory, normativve, and theese three induustries, trend analysis wass frequently used u in suubjective apprroaches , w we drew treemmap for TF methods m infformation tecchnology inddustry, whereeas descriptivve and annd their type. In here, expploratory apprroaches are outward o maatrices metho ods were applied to material industrry and International Scholarly and Scientific Research & Innovation 7(4) 2013 593 scholar.waset.org/1999.8/2934 World Academy of Science, Engineering and Technology International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering Vol:7, No:4, 2013 monitoring an nd intelligennce methods were utilizzed in 33. Ratio off Subjective, Exploratory y, and Norrmative telecommunicaation services. Meanwhile, in the other ind dustries, Appproaches in each e Industry m most frequenttly used methods m were monitoring g and in ntelligence methods, trend d analysis, and a descriptivve and matrices metho ods in principple. Also, statistical methoods and exxpert opinion methods weree applied to almost a every industry paartly. Howeveer, there is no o TF method applied in fin nancials in ndustry. 2. Ratio of Quantitative Q annd Qualitativee Approaches in each In ndustry International Science Index, Industrial and Manufacturing Engineering Vol:7, No:4, 2013 waset.org/Publication/2934 F Fig. 7 Pie chart for ratio of expploratory, norm mative, and subjeective approachess in each industrry In terms off classificatioon scheme of o TF metho ods as exp ploratory, normative, and subjective ap pproaches, thee most appplied approaaches across almost eveery industry were exp ploratory appproaches. Thiss is because thet purpose off TF is maainly on the detection d of ppast, present, and a future treends of tecchnology, not on the considderation of the normative vaalue for Fiig. 6 Pie chart fo or the ratio of quuantitative and qualitative app proaches futture direction of technologyy. in eaach industry However, in some s industriees such as heaalthcare industtry and tellecommunicattion services, the normativ ve value for future In this part, ratio r of quanttitative and qu ualitative apprroaches dirrection of tech hnology shouldd be considereed for the welll-being n each technolo in ogy industry w was investigatted. Except fin nancials off human societty. For this reaason, normatiive approachees were in ndustry, 9 indu ustries were investigated. i Overall, quanntitative useed in some deegree for thesse industries compared c with h other appproaches were well used acrossa many teechnology ind dustries. inddustries. Typical indu ustries applieed quantitativve approachees were in nformation tecchnology, eneergy, telecom mmunication service, s IV. CONCLUSIONS AND FUTURE RESEARCH annd health carre. These in ndustries are relatively high-tech in ndustries, so advances a in th hese industriess have been made m in Main contribu ution of this study is to profile developm ments in reecent years. In I addition, because of technology-in t ntensive an nd patterns of o scholarly research in TF over tim me and chharacteristics of high-techh service in ndustries, qua alitative inv vestigate whicch technologyy industries haave used certtain TF appproaches dep pending on su ubjective opinnions were som mewhat meethod. The maajor findings ccan be summaarized as follow ws: haard to be appllied. Instead, quantitative approaches a baased on 1. There has been a steaddy growth in the number of TF th he analytic reesult of dataa about detail characterisstics of blished in jourrnal, especiallly during the last 10 articles pub technologies were w preferredd to forecast trend t of compplicated years (20044-2013). hiigh-tech servicce industries. 2. TF Researcch has mainlly used quan ntitative approaches Meanwhile, qualitative approaches a were w used in several compared with w qualitativve approachess. in ndustries succh as materrial, industriaals, and co onsumer 3. Exploratoryy approachess such as Deelphi, curve fitting, diiscretionary. These inddustries havee some co ommon DEA, techn nology roadm map were frequ uently used annd also chharacteristics. First, thesse industries are related d with normative approaches a suuch as patentt analysis and d TRIZ m manufacturing, not service. Second, largee-scale capitall goods were somew what used. arre mainly pro oduced in theese industries and, so, boo om and 4. Information n technology, materials, and d telecommun nication reecession of th hese industriees are greatly y affected by global services haave received most researrch attention as an ecconomic climate. Because of this, experrt opinions arre more application area of TF. neeeded to foreccast technologgy trend by reeflecting situaation of 5. Monitoring g and intelligeence methods, trend analyssis, and th he world econ nomy. For theese reason, qu ualitative apprroaches descriptive and matricess methods weere most freq quently w well used in these indusstries. were used metho ods across almmost industries. International Scholarly and Scientific Research & Innovation 7(4) 2013 594 scholar.waset.org/1999.8/2934 World Academy of Science, Engineering and Technology International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering Vol:7, No:4, 2013 6. Quantitative approaches tended to be applied in high-tech service industries, whereas qualitative approaches tended to be applied in industries related with large-scale capital goods. 7. Exploratory approaches are the most frequently used approaches across almost every industry. Meanwhile, normative approaches were mostly applied in healthcare industry and telecommunication services. Despite all major findings and contributions of this study, it has several limitations that suggest paths for our future research. First, this study investigated TF related articles mainly focusing on journal papers. Therefore, other sources containing TF topic such as magazine, proceedings of conferences, and various books can be investigated to provide more fruitful information. Second, this study only covered application area of TF methods. Strength and weakness of TF methods for selecting International Science Index, Industrial and Manufacturing Engineering Vol:7, No:4, 2013 waset.org/Publication/2934 complementary and appropriate TF for a certain technology industry can be provided in future research. ACKNOWLEDGMENT This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (2012R1A1A1041265). REFERENCE S. Mishra, S. Deshmukh, P. Vrat, Matching of technological forecasting technique to a technology, Technol. Forecast. Soc. Chang., 69 (2002) 1-27. H. Ernst, The use of patent data for technological forecasting: the diffusion of CNC-technology in the machine tool industry, Small Business Economics, 9 (1997) 361-381. A. Firat, W. Woon, S. Madnick, Technological Forecasting–A Review, in, Composite Information Systems Laboratory (CISL), Massachusetts Institute of Technology, 2008. S. Jun, A Forecasting Model for Technological Trend Using Unsupervised Learning, Database Theory and Application, Bio-Science and Bio-Technology, (2011) 51-60. A.L. Porter, S.W. Cunningham, J. Banks, A.T. Roper, T.W. Mason, F.A. Rossini, Forecasting and management of technology, Wiley, 2011. H. Dransfeld, J. Pemberton, G. Jacobs, Quantifying weighted expert opinion: the future of interactive television and retailing, Technol. Forecast. Soc. Chang., 63 (2000) 81-90. S. Jun, S.S. Park, D.S. Jang, Technology forecasting using matrix map and patent clustering, Industrial Management & Data Systems, 112 (2012) 786-807. M. Fattori, G. Pedrazzi, R. Turra, Text mining applied to patent mapping: a practical business case, World Patent Information, 25 (2003) 335-342. S. Lee, B. Yoon, Y. Park, An approach to discovering new technology opportunities: Keyword-based patent map approach, Technovation, 29 (2009) 481-497. M.S. Slocum, C.O. Lundberg, Technology Forecasting: from emotional to empirical, Creativity and Innovation Management, 10 (2001) 139-152. J.P. Martino, A review of selected recent advances in technological forecasting, Technol. Forecast. Soc. Chang., 70 (2003) 719-733. B. Johnson, TreeViz: treemap visualization of hierarchically structured information, in: Proceedings of the SIGCHI conference on Human factors in computing systems, ACM, 1992, pp. 369-370. L. Shvartz, R. Horesh, B. Raz, The logistic envelope approximation in technological forecasting, Technol. Forecast. Soc. Chang., 19 (1981) 283-289. International Scholarly and Scientific Research & Innovation 7(4) 2013 595 scholar.waset.org/1999.8/2934

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