Assessing performance factors for a 3PL in a value chain Gulgun Kayakutlu, Gulcin Buyukozkan n Galatasaray University, Istanbul 34357, Turkey a r t i c l e i n f o Article history: Received 27 February 2009 Accepted 12 October 2010 Available online 31 December 2010 Keywords: Third party logistics (3PL) companies Logistics performance factors Analytic network process Value chain performanc e a b s t r a c t Business continuity of the logistics companies in the twenty first century highly depends on the value chai n perfo rmance. As the varie ty of servi ces outs ourc ed to thirdparty logis tics(3PL) comp anie s incre ase, success strategies for these companies are to be revised. This study explores and illustrates an analytical framework to assess the performance factors for 3PL companies through a managerial view. The factors integ ratin g the strat egica l and oper ational targe ts are evaluatedwithin a frame work based onfourlevels; performance targets, planning activities, logistics operations, and performance attributes of logistics opera tions . The anal ytic netwo rk proce ss is used to deter mine the most effec tive perfor mance attributes. The framework is applied and studied in two major logistics companies active in the South East Europe. The proposed framework will contribute to the logistics sector by demonstrating the paradigm shift in performance measurement. & 2011 Published by Elsevier B.V. 1. Intro duct ion Increasing requests for logistics services imposed a strategic role for the third party logistics (3PL) companies. It has been emphasised by many researchers that supply chain will not be effective unless logi stic s firms do notmeasureand moni torthe comp any per formance in a flo w offunct ion s ra the r tha n ind ivi du al act ivi tie s ( Robe rtso n et al., 2002). T he b igges t pa ce is take n by inte grat ed evaluation of info rma - tio n andmaterial flow( Guna sekaran and Ngai , 2003 ).It issho wnby a recent literature survey on logistics and supply chains that there is still a big gap on reconsidering inter-functional and inter-company measures (Sachan and Datta, 2005). These gaps are advocated by concentration of 3PL companies on outsource requests; which are focus ed on eva lua tio n of ser vic e pr ovider ona sin gle function suc h as transpor tation and warehousin g ( Jharkharia and Shankar, 2007). The need for di fferentiati ng pro po sed ser vic es cau sed ma nag ers to ask for quantitative performance scores ( Cook and Bala, 2007). Hence, there is a necessity of considering variations arising across the domain of‘‘ef fect ive fact ors’ ’ (Par hizga ria and Gilbert, 2004 ); as we ll as inte gr at - ing supp ly chainmanagement and logi stic s mana geme nt ( Kim,2009). In the pro duct ion eco nomy and busi ness str ate gy lit erature, considerable interest has been centred on identifying the domain ofeff ective fact ors . App roa ches show a var iety of dimensi ons in defi nin g the success, such as quality and organisational interactions ( Cheng et al., 2005), integra ting network and operat ional strategies (Rudberg and Olhaberg, 2003), relating marketing performanc e and human capital (Knemeyer and Murphy, 2004), supply chain strategies and logistics operations (Lai et al., 2004; Liu and Ma, 2005; Jayaram and Tan, 2010). First generic covering was realised by Yamin et al. (1999). Since then , ther e hasbeen some indu str y spe cificanalys is as theone on automotive logistics by Schmitz and Platts (2004), Krakovics et al. (2008) and in food processing as in Hsiao et al. (2010) . Today the altitude of performance is defined by core compe- tencein netwo rks,process orien tatio n, freemargins,organisat ional learn ing and techn ology utilisati on as Gunasekaran and Ngai (2007) specifies. To create competitive advantages based on these new fiel ds of foc us, det ail ed fac tors var y by industry. De Sensi et al . (2007) makes an introduction to the industry specified issues in beverage supply chains. Singh et al. (2005) make the analysis in automotive indus try of Austr alia. The article ofLaiet al. (20 07) take the issues in 3PL companies considering the clusters in China. Sout h East Europe has become an impo rta nt hub for logis tic services between Asia and Europe. Hence, 3PL logistics companies giving services through Europe are in the process of changing the busin esspara dig m. Thi s is thefirst stu dy that wil l disco verthe fac tors that need to be considered in competitive strategy reengineering by Turkish partnered companies that take role in this important route. This study has two main objectives: (1) define a model to analyse the effectiveness of a variety of factors that will link strategical and operational targets using Analytic Network Process (ANP); (2) apply the framework to compare effectiveness of the factors in two major 3PL compan ie s of So ut h East Europe wit h di ff erent strateg ies . Managers of the companies surveyed are in the process of changing the strategies and have not yet determined exact responses for the business questions. It is an obligation to prepare and present a pool of fact ors affe ctin g the compet itiv e strate gies and the n stud y the int erd epe nde ncie s and eff ecti veness of tho se fact orsfor thecompan ies studied. Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/ijpe Int. J. Production Economics 0925-5273 /$ - see front matter & 2011 Published by Elsevier B.V. doi:10.1016/j.ijpe.2010.12.019 n Corresponding author. Fax: +90 212 259 5557. E-mail address: [email protected] (G. Buyukozkan). Int. J. Production Economics 131 (2011) 441–452
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models for solutions. It is observed that strategic goals embracing
competitive advantage in a supply chain can be classified in three
groups: networking, capital balancing and customer focus. Effective
planning enables linking these strategies with different logistics
operations. There is a big variety of measure for operational perfor-
mance. Besides, control and coordination of planning will feed in the
right information for the related strategies (Liu and Ma, 2005). This
section is organised to handle performance factors at strategic,
planning and operationallevel and the summary of literature analysis
is given in Table 1a.
2.1.1. Performance targets
The evolution in information sciences lead majority of academic
studiesto focus on business networkissues. Boyson et al. (1999) is one
of the initiators of discussion on alliance relationship in distribution
networks being as influential as cost management. Business alliancesconsider distribution channels as well as supplier and partner
relations. Stock et al. (2000) detail the issues of distributors in a
supply chain, emphasising that performance influencers are not only
configuration and organisation of the chain, as mentioned by
Jayaraman and Ross (2003), but real partnering in planning, pricing
and services. Dubois and Gadde (2000) reveal the innovation and
efficiency advances by partnering with suppliers. Ross and Droge
(2004) worked on strategies and operations effected by supply chain
efficiencies. It is analytically observed that effectivebusiness network
would grant strategic enhancements as well as operational efficiency
improvements. Most recently each operation is tested in detail to
realise the integration (Dong and Chen, 2005; Biehl et al., 2007). It is
observed that the supply chain is to be designed based on structural
and relational coordination criteria as stated by Truong and Azadivar
(2005). Kim (2009) gets into the details of supply chain management
influences on structured and unstructured integration of strategies
and logistics operations.
Since logistics is a value adding industry, capital balancing is an
important target specifically in developing countries (Clark et al.,
1993). One of the major operations of logistics, inventory manage-
ment needs special interest in strategic and operation planning
since it is a highly capital binding operation. Bonney (1994)
analysed how capital performance is interacted with the balance
of pull and push strategies of inventorymanagement. DeSensi etal.
Table 1a
Summary of literature review.
Performance
factors
Relevant focus Main references
Strategic targets
Networking Distribution network Stock et al. (2000), Jayaraman and Ross (2003), Liu and Ma (2005), Sachan and Datta (2005)
Logistics chain (network) Boyson et al. (1999), Dong and Chen (2005)
Supply chain (network) Dubois and Gadde (2000), Ross and Droge (2004), Truong and Azadivar (2005), Biehl et al. (2007), Kim (2009),
Jayaram and Tan (2010).
Capital balance Structural capital Gunasekaran et al. (2005), De Sensi et al. (2007)
Human capital Clark et al. (1993), Rudberg and Olhaberg (2003), Knemeyer and Murphy (2004), Gunasekaran et al. (2005)
Financial capital Clark et al. (1993), Bonney (1994), Ross (2000), Gunasekaran et al. (2005), Krakovics et al. (2008)
Relational capital Zhao and Stank (2003), Gunasekaran et al. (2005)
Customer focus Quality-customer satisfaction Andersson et al. (1989), Fawcett and Cooper (1998), Korpela and Lehmusvaara (1999), Ross (2000),
Goetschalckx et al. (2002), Rudberg and Olhaberg (2003)
Mass customisation Rabinovich et al. (2003)
Customer capital Barad and Sapir (2003), Lai and Lee (2003), Zhao and Stank (2003), Parhizgaria and Gilbert (2004), Kuˇ sar et al.(2005), Krakovics et al. (2008)
Customer segmentation Mentzer et al. (2004), Kuˇ sar et al. (2005)
Demand chain Landeghem and Vanmaele (2002), Treville et al. (2004), Cheng et al.(2005), Hsiao et al., (2010).
Accredited customers Bottani and Rizzi (2006)
Planning activities
Strategies Technology/organisation Andersson et al. (1989), Hameri and Paatela (1995), Schmitz and Platts (2004), Kim (2009).
Alliances/customers Robertson et al. (2002), Hertz and Alfredsson (2003), Georgiadis et al. (2005), Sachan and Datta (2005)
New product/services Hertz and Alfredsson (2003), Rudberg and Olhaberg (2003)
Resources Distribution centres Toppen and Smits (1998), Gunasekaran and Ngai (2003), Zhao and Stank (2003), Bogataj and Bogataj (2004),
Ross and Droge (2004), Georgiadis et al. (2005), Krakovics et al. (2008), Hsiao et al., (2010)
Delivery vehicles Toppen and Smits (1998), Ross and Droge (2004), Georgiadis et al. (2005), Ioannou (2005)
Employees Gunasekaran and Ngai (2003), Cook and Bala (2007), Ioannou (2005)
Information Strategic planning Yamin etal. (1999), Gunasekaranand Ngai(2003, 2004), Yusufet al.(2004), Bayraktar et al. (2009), Kim (2009).
Operational planning Toppen and Smits (1998), Au et al. (2002), Kim and Narasimhan (2002), Landeghem and Vanmaele (2002),
Rabinovich et al. (2003), Kim (2009).
Measurement Irani et al. (2006), Hamdan and Rogers (2008)
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