DOI 10.1007/s13198-014-0283-9
ORIGINAL ARTICLE
Strategic business unit ranking based on innovation performance: a case study of a steel manufacturing company
Behrooz Noori
Received: 15 January 2014 / Revised: 27 June 2014
Ó The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and
Maintenance, Lulea University of Technology, Sweden 2014
Abstract Corporations may be composed of multiple strategic business units (SBUs), each of which is responsible for its own profitability. Innovation performance management of SBUs boosts corporation business results.
In the present work, SBU ranking based on innovation performance was addressed. The contribution of the proposed model was threefold: (1) it proposed a fuzzy analytic hierarchy process (AHP) for SBU ranking; (2) it provided a comprehensive and systematic framework that combined balanced scorecard (BSC) and fuzzy AHP; and (3) it explored practical application and illustrated the efficacy of the procedures and algorithms. It used a real-world case study in a large steel manufacturing company to present the applicability of the system. Finding SBU priorities would help the corporations to develop strategies and policies to manage and improve SBU performance.
Keywords Strategic business unit Á Innovation performance management Á SBU performance Á Balanced scorecard Á Fuzzy analytic hierarchy process Á Steel sector
1 Introduction
Despite the advances in technology and innovation, many of companies do not measure or assess innovation performance and do not have an internal system to measure innovation performance (Hamel 2006). In the current economic situation, innovation is a high strategic priority
B. Noori (&)
Department of Industrial Engineering, West Tehran Branch,
Islamic Azad University, Tehran, Iran e-mail: Bnoori@gmail.com
for most companies, and many see it as a strong contributor to growth. Yet, many also struggle
References: Alegre J, Chiva R, Lapiedra R (2009) Measuring innovation in long product development cycle industries: an insight in biotechnology Amiran H, Radfar I, Zolfani SH (2011) A fuzzy MCDM approach for evaluating steel industry performance based on balanced scorecard: a case in Iran international conference on emergency management and management sciences (ICEMMS( Bentes AV, Carneiro J, da Silva JF, Kimura H (2012) Multidimensional assessment of organizational performance: integrating BSC and AHP. J Bus Res 65(12):1790–1799 Bigliardi B, Dormio AI (2010) A balanced scorecard approach for R&D: evidence from a case study. Facilities 28(5):278–289 Bu¨yu¨ko¨zkan G, C¸ifc¸i G, Gu¨leryu¨z S (2011) Strategic analysis of Cebeci U (2009) Fuzzy AHP-based decision support system for selecting ERP systems in textile industry by using balanced scorecard. Expert Syst Appl 36(5):8900–8909 Cebeci U, Sezerel B (2008) Performance evaluation model for R&D intelligent system and knowledge engineering 1 1276–1281 Chan YL (2006) An analytic hierarchy framework for evaluating Chan FTS, Kumar N (2007) Global supplier development considering risk factors using fuzzy extended AHP-based approach 35(4):417–431 Chan V, Musso C, Shankar V (2008) Assessing innovation metrics. Chang D-Y (1992) Extent analysis and synthetic decision. Optim Tech Appl 1:352–355 Chang D-Y (1996) Applications of the extent analysis method on fuzzy AHP Chen C, Chen P (2009) An evaluation of innovation performance based on fuzzy interval linguistic variables 26(5):387–396 Cho C, Lee S (2011) A study on process evaluation and selection Cho DW, Lee YH, Ahn SH, Hwang MK (2012) A framework for measuring the performance of service supply chain management. Comput Ind Eng 62(3):801–818 Damanpour F (1991) Organizational innovation: a meta-analysis of effects de Ven V, Andrew H (1986) Central problems in the management of innovation Dervitsiotis KN (2010) A framework for the assessment of an organisation’s innovation excellence Excell 21(9):903–918 Grigoroudis E, Orfanoudaki E, Zopounidis C (2012) Strategic 40(1):104–119 Haghighi M, Divandari A, Keimasi M (2010) The impact of 3D Hamel G (2006) The why, what, and how of management innovation. Harvard Bus Rev 84(2):72 Han J, Kim N, Srivastava R (1998) Market orientation and Huang HC (2009) Designing a knowledge-based system for strategic planning: a balanced scorecard perspective 36(1):209–218 Huang HC, Lai MC, Lin LH (2011) Developing strategic measurement and improvement for the biopharmaceutical firm: using the BSC hierarchy. Expert Syst Appl 38(5):4875–4881 Hult G, Hurley R, Knight G (2004) Innovativeness: its antecedents Jovanovic J, Krivokapic Z (2008) AHP in implementation of Balanced Scorecard Kahraman C, Cebeci U, Ruan D (2004) Multi-attribute comparison ofcatering service companies using fuzzy AHP: the case of Turkey. Int J Prod Econ 87(2):171–184 Kaplan RS, Norton DP (1992) The balance scorecard – Measures that drive performance. Harvard Bus Rev 70(1):71–79 Kaplan RS, Norton DP (1993) Putting the balanced scorecard to work. Harvard Bus Rev 71(5):134–140 Kaplan RS, Norton DP (1996) Using the balance scorecard as a strategic management system. Harvard Bus Rev 74(1):75–85 Kilincci O, Onal SA (2011) Fuzzy AHP approach for supplier Kunz H, Schaaf T (2011) General and specific formalization approach for a Balanced Scorecard: an expert system with application in health care. Expert Syst Appl 38(3):1947–1955 Kutlu AC, Ekmekc¸iog˘lu M (2012) Fuzzy failure modes and effects Lazzarotti V, Manzini R, Mari L (2011) A model for R&D performance measurement Lee AHI, Chen W, Chang CJ (2008) A fuzzy AHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Taiwan Leung L, Lam K, Cao D (2006) Implementing the Balanced Scorecard using the Analytic Hierarchy Process and the Analytic Network Process. J Oper Res Soc 57(6):682–691 OECD (1994) Main definitions and conventions for the measurement