Are ICTs Really That Important in Driving Industry Performance?

A decision tree is used to investigate how information and communication technologies (ICTs) and financial factors influence the performance of service and manufacturing industries globally. Industry performance is measured by average fixed asset purchases among firms at the industry level. In addition, industry sectors and geographic regions are included in the predictive model. The results show that financial factors are better predictors of performance than ICT factors. For example, access to bank loans or lines of credit is by far the best predictor among the variables included in the study. Having a website is the only ICT factor among the top five predictors. Geography also plays an important role in predicting industry performance.

[1]  Delvin Grant,et al.  Exploring the effects of ICTs, workforce, and gender on capacity utilization , 2019, Inf. Technol. Dev..

[2]  Thomas Hempell,et al.  Ict, Innovation and Business Performance in Services: Evidence for Germany and the Netherlands , 2004 .

[3]  H. Broadman,et al.  Finance and Growth: Schumpeter Might Be Right , 1993 .

[4]  Igor Garnik Building website credibility: a prospective solution to e-Commerce in Poland , 2004, CHI EA '04.

[5]  Gordon Newlove Asamoah,et al.  The Impact Of The Financial Sector Reforms On Savings, Investments And Growth Of Gross Domestic Product (GDP) In Ghana , 2011 .

[6]  Lorin M. Hitt,et al.  Productivity, Business Profitability, and Consumer Surplus: Three Different Measures of Information Technology Value , 1996, MIS Q..

[7]  J. J. Po-An Hsieh,et al.  Addressing Digital Inequality for the Socioeconomically Disadvantaged Through Government Initiatives: Forms of Capital That Affect ICT Utilization , 2011, Inf. Syst. Res..

[8]  J. March,et al.  Organizational Performance as a Dependent Variable , 2016 .

[9]  Kevin Crowston,et al.  Information technology and the transformation of industries: three research perspectives , 2004, J. Strateg. Inf. Syst..

[10]  David Gago,et al.  Innovation and ICT in service firms: towards a multidimensional approach for impact assessment , 2007 .

[11]  Gilberto Libanio,et al.  1 MANUFACTURING INDUSTRY AND ECONOMIC GROWTH IN LATIN AMERICA : A KALDORIAN APPROACH , 2007 .

[12]  Dale W. Jorgenson,et al.  Computers And Growth , 1995 .

[13]  Mohamed Kossaï,et al.  Adoption of information and communication technology and firm profitability: Empirical evidence from Tunisian SMEs , 2014 .

[14]  Benjamin Yeo,et al.  A global perspective on tech investment, financing, and ICT on manufacturing and service industry performance , 2018, Int. J. Inf. Manag..

[15]  Benjamin Yeo,et al.  Exploring the factors affecting global manufacturing performance* , 2019, Inf. Technol. Dev..

[16]  Benjamin B. M. Shao,et al.  Total factor productivity growth in information technology services industries: A multi-theoretical perspective , 2014, Decis. Support Syst..

[17]  Syahriah Bachok,et al.  Understanding Domestic and International Tourists’ Expenditure Pattern in Melaka, Malaysia: Result of CHAID Analysis , 2015 .

[18]  Flora Ma Diaz-Perez,et al.  CHAID algorithm as an appropriate analytical method for tourism market segmentation , 2016 .

[19]  A. Molla Downloading or uploading? The information economy and Africa's current status , 2000 .

[20]  L. Vidaur,et al.  Procalcitonin (PCT) levels for ruling-out bacterial coinfection in ICU patients with influenza: A CHAID decision-tree analysis. , 2016, The Journal of infection.

[21]  Benjamin Yeo,et al.  Predicting service industry performance using decision tree analysis , 2018, Int. J. Inf. Manag..

[22]  Morena Paulišić,et al.  The OTAs' Websites: The Opinion of Generation Y Leads to Organizational Change , 2015 .

[23]  C. Comiskey,et al.  Using chi-Squared Automatic Interaction Detection (CHAID) modelling to identify groups of methadone treatment clients experiencing significantly poorer treatment outcomes. , 2013, Journal of substance abuse treatment.

[24]  Mohamed Kossaï,et al.  The Relationship between Information and Communication Technology Use and Firm Performance in Developing Countries: A Case Study of Electrical and Electronic Goods Manufacturing SMEs in Tunisia , 2013 .

[25]  Dallen J. Timothy,et al.  Understanding Japanese tourists’ shopping preferences using the Decision Tree Analysis method , 2011 .

[26]  John R. Baldwin,et al.  Selection Versus Evolutionary Adaptation: Learning and Post- Entry Performance , 1995 .

[27]  Moon-Koo Kim,et al.  Investigating factors influencing the market success or failure of IT services in Korea , 2017, Int. J. Inf. Manag..

[28]  S. Cecchini,et al.  Can information and communications technology applications contribute to poverty reduction? Lessons from rural India , 2003 .

[29]  Heiko Gebauer,et al.  ICT as a catalyst for service business orientation , 2013 .

[30]  Dale W. Jorgenson,et al.  U.S. Economic Growth at the Industry Level , 2000 .

[31]  Raymond W. Goldsmith,et al.  Financial Structure and Development , 1970 .

[32]  Patrick Legohérel,et al.  Variety-seeking: Using the CHAID segmentation approach in analyzing the international traveler market , 2015 .

[33]  Kweku-Muata Osei-Bryson,et al.  The Impacts of Telecommunications Infrastructure and Institutional Quality on Trade Efficiency in Africa , 2015, Inf. Technol. Dev..

[34]  G. F. Nel,et al.  Corporate websites in Africa: Has online investor relations communication improved during the past four years? Evidence from Egypt, Kenya, Morocco, Nigeria and Tunisia , 2011 .

[35]  Mevlut Ture,et al.  Using Kaplan-Meier analysis together with decision tree methods (C&RT, CHAID, QUEST, C4.5 and ID3) in determining recurrence-free survival of breast cancer patients , 2009, Expert Syst. Appl..

[36]  Mary Jo Bitner,et al.  Services Marketing: Integrating Customer Focus Across the Firm , 1996 .

[37]  Jaime H. Nunez,et al.  On the applicability of a computer model for business performance analysis in SMEs: A case study from Chile , 2000 .

[38]  James G. March,et al.  Crossroads---Organizational Performance as a Dependent Variable , 1997 .

[39]  Mark A. Vonderembse,et al.  The evolution of manufacturing systems: Towards the post-industrial enterprise , 1991 .

[40]  M. Välimäki,et al.  Barriers and facilitators influencing the implementation of an interactive Internet-portal application for patient education in psychiatric hospitals. , 2008, Patient education and counseling.

[41]  Felix Bollou,et al.  ICT Infrastructure Expansion in Sub-Saharan Africa: An Analysis of Six West African Countries from 1995 to 2002 , 2006 .

[42]  Melius Weideman,et al.  An empirical study on website usability elements and how they affect search engine optimisation : original research , 2011 .

[43]  Rajiv Kohli,et al.  Measuring Information Technology Payoff: A Meta - Analysis of Structural Variables in Firm - Level Empirical Research , 2003, Inf. Syst. Res..

[44]  Olawale Femi Kayode,et al.  THE INTERACTIVE WHITEBOARD IN ENGLISH AS A FOREIGN LANGUAGE (EFL) CLASSROOM , 2012 .

[45]  Mdj Michael Antioco Service orientations of manufacturing companies : impact on new product success , 2006 .

[46]  Rajiv Kohli,et al.  Information Technology Payoff in the Health-Care Industry: A Longitudinal Study , 2000, J. Manag. Inf. Syst..

[47]  Paul M. Mather,et al.  An assessment of the effectiveness of decision tree methods for land cover classification , 2003 .

[48]  Roya Gholami,et al.  Time series analysis in the assessment of ICT impact at the aggregate level - lessons and implications for the new economy , 2005, Inf. Manag..

[49]  Shinichiro Koga,et al.  A prediction rule for the development of delirium among patients in medical wards: Chi-Square Automatic Interaction Detector (CHAID) decision tree analysis model. , 2013, The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry.

[50]  Mary O'Mahony,et al.  Productivity, Workplace Performance and ICT: Industry and Firm-Level Evidence for Europe and the Us , 2005 .

[51]  Thomas Hempell,et al.  ICT, Innovation and Business Performance in Services , 2004 .

[52]  Guido Schryen,et al.  Revisiting IS business value research: what we already know, what we still need to know, and how we can get there , 2013, Eur. J. Inf. Syst..

[53]  Erik Brynjolfsson,et al.  The intangible benefits and costs of investments: evidence from financial markets , 1997, ICIS '97.

[54]  P. Akpan Basic-needs to globalization: Are ICTs the missing link? , 2003 .

[55]  Kweku-Muata Osei-Bryson,et al.  Advances in Research Methods for Information Systems Research: Data Mining, Data Envelopment Analysis, Value Focused Thinking , 2013 .

[56]  Roy Thurik,et al.  Market dynamics in the Netherlands: Competition policy and the role of small firms , 2001 .

[57]  Nikolaos Eriotis,et al.  Profit Margin And Capital Structure: An Empirical Relationship , 2011 .

[58]  Kenneth L. Kraemer,et al.  Information technology and economic performance , 2003, ACM Comput. Surv..

[59]  Héctor Alberto Botello,et al.  Las Tecnologías De La Información Y La Comunicación Y El Desempeño De Las Firmas: Evidencia De Las Firmas Industriales Del Ecuador (The Information Technology and Communication and Firm Performance: Evidence from Firms Industrialists Ecuador) , 2014 .

[60]  D. Wood Measuring Corporate Social Performance: A Review , 2010 .

[61]  Sinan Aral,et al.  I.T. Assets, Organizational Capabilities and Firm Performance: Do Resource Allocations and Organizational Differences Explain Performance Variation? , 2007 .

[62]  T. Beck,et al.  Financial and Legal Constraints to Growth: Does Firm Size Matter? , 2005 .

[63]  Maung K. Sein,et al.  Conceptualizing the ICT Artifact: Toward Understanding the Role of ICT in National Development , 2004, Inf. Soc..