Developing retailer selection factors for collaborative planning, forecasting and replenishment
| Published date | 10 August 2015 |
| Pages | 1292-1324 |
| Date | 10 August 2015 |
| DOI | https://doi.org/10.1108/IMDS-01-2015-0009 |
| Author | Farhad Panaihfar,Cathal Heavey,PJ Byrne |
| Subject Matter | Information & knowledge management,Information systems,Data management systems |
Developing retailer selection
factors for collaborative
planning, forecasting
and replenishment
Farhad Panaihfar and Cathal Heavey
Department of Design and Manufacturing Technology,
Enterprise Research Centre, University of Limerick, Limerick, Ireland, and
P.J. Byrne
Dublin City University Business School, Dublin City University, Dublin, Ireland
Abstract
Purpose –Selecting an appropriate partner is a vital and strategic decision-making process in any
supply chain collaboration initiative. The purpose of this paper is to introduce and explore the key
factors considered by manufacturers in the selection of an appropriate retailer(s) for collaboration and
collaborative planning, forecasting and replenishment (CPFR) implementation and the relationships
between these factors.
Design/methodology/approach –A comprehensive literature review and experts’views are applied
to identify the main retailer selection and evaluation factors for CPFR implementation. A fuzzy
decision-making trial and evaluation laboratory approach is then used to rank and analysis the
interaction among identified factors. The findings are finally evaluated using a case study from a
high-tech industry.
Findings –The most important partner selection factors comprising of five dimensions and 24 factors
are introduced. Of the identified criteria, three factors: manufacturer’s familiarity with the retailer,
workforce skills and training and customer service orientation and capability have been identified as
critical when selecting retailers for CPFR implementation. The technological capabilities dimensions
are identified as the only net cause dimension which affects all other dimensions and its importance
and role in simplifying and enhancing the speed and flexibility of CPFR implementation.
Practical implications –The paper identifies practical retailer selection factors for CPFR
implementation and the causal relationships between factors. Developed retailer selection dimensions
and criteria will assist manufacturers and retailers in understanding the role these factors play in
CPFR implementation. This will also assist in appropriate retailer(s) selection by manufacturers.
Originality/value –This paper contributes to the literature on CPFR and tackles the important issue
of selecting appropriate partners by developing retailer selection dimensions and criteria in CPFR
implementation.
Keywords Partnership, Fuzzy DEMATEL, CPFR implementation, Retailer selection factor
Paper type Research paper
1. Introduction
Collaboration and collaborative planning, forecasting and replenishment (CPFR) in the
context of supply chains have been well discussed in previous research (Holmström et al.,
2002; Sahay, 2003; Daugherty et al., 2006; VICS, 2013; Byrne and Heavey, 2006; Thomé and
Hollmann, 2014; Panahifar et al., 2014, 2015a). It is well recognised that collaboration
between supply chain members can facilitate enhanced strategic and operational focus,
thus allowing individual organisations to better exploit their core competencies (Daugherty
et al., 2006). Sahay (2003) identified three major types of collaborative relationships:
manufacturing/supplier collaboration; manufacturing/customer (i.e. retailers) collaboration
Industrial Management & Data
Systems
Vol. 115 No. 7, 2015
pp. 1292-1324
©Emerald Group Publishing Limited
0263-5577
DOI 10.1108/IMDS-01-2015-0009
Received 10 January 2015
Revised 20 March 2015
15 May 2015
Accepted 12 June 2015
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
1292
IMDS
115,7
and collaboration with third and fourth party logistics providers, with the manufacturer-
retailer collaboration identified as the most significant. Sahay (2003, p. 77) argued that
“the main focus in this collaboration is developing an understanding of demand at the
point of consumption, followed by the creation of a mutually agreed replenishment plan”.
CPFR has also been acknowledged as one of the most important collaborative initiatives
in business to business commerce potentially leading to radically reduced inventories and
expenses while simultaneously improving customer service (VICS, 2013). Although
promising results have been presented in relation to CPFR applications, significant
implementation challenges still exist, which has led to slower than expected uptake rates
(Panahifar et al., 2015a).
A review of the importance of partner selection in successful collaboration practices
suggests that there is a strong correlation between the selection of the most suited
partner(s) and the main barriers to a successful collaborative approach, including: lack
of trust –Min et al. (2005); lack of compatibility of partners’abilities –Panahifar et al.
(2014); cultural conflicts –Kelly et al. (2002). In general, improper partner selection is
recognised as one the main reasons for below standard performance in trading
partnerships (Ireland et al., 2002). Whilst it is recognised that selection of appropriate
partners is a critical, complex and time consuming task in CPFR (Sheffi, 2002; Fu et al.,
2010), it has been under represented in the academic literature to date with only a small
number of papers covering the topic (Chung and Leung, 2005; Panahifar et al., 2014).
This has led to a gap in the knowledge base relating to the identification and selection
of appropriate implementation partners so as to maximise the likelihood of CPFR
success. This study explicitly addresses this gap through retailer selection factor
analysis for CPFR, including factor identification, ranking and interaction ide ntification
using a hybrid approach including expert opinion. A review of previous literature
shows that while there are many partner selection factors affecting collaboration, from
a practice-based perspective more efforts should be made to include expert opinion in
the evaluation and distillation of such factors. In this study, this process uses a detailed
literature review to identify the most significant factors which positively affect a
manufacturer’s ability to collaborate with retailers. In order to build on this and to
capture practice-based omissions from the literature, expert views were then used to
assess the identified factors and to alter and adapt as appropriate based on their
practice expertise.
Traditionally, multi-criteria decision making (MCDM) methods have been
widely used in partner selection, (Huang and Keskar, 2007). In this study a hybrid
version of one such technique is used to evaluate the relevant partner selection
factors, the decision-making trial and evaluation laboratory (DEMATEL) method.
The DEMATEL model has been successfully applied in many fields and areas,
such as outsourcing, project management and marketing including the use of
fuzzy DEMATEL in partner selection and evaluation studies (Chang et al., 2011;
Liou, 2012).
The remainder of this study is organised as follows. Section 2 presents the
methodology by which this study was completed, expanding on factor selection and
refinement through literature review and expert opinion, followed by fuzzy DEMATEL
evaluation and concluding with a case validation. Following this, Section 3 presents
results for each of the methodological steps and discusses the industrial validation of
the results in the high-tech industry case organisation. Sections 4 and 5, respectively
discusses the results followed by concluding remarks identifying their theoretical and
practical implications.
1293
Retailer
selection
factors for
CPFR
2. Methodology
High-tech industries such as semiconductor, computer and peripheral equipment,
telecommunications, pharmaceutical and medical devices are characterised by rapid
change, intense competition and a highly uncertain environment (Huang and Lin, 2006).
These characteristics lead to severe difficulties in relation to demand forecasting
for high-tech products even in what can be regarded as stable economies (Wu et al.,
2005), leading to organisational underperformance. In such instances, high levels of
collaboration between supply chain partners (e.g. CPFR) have been proposed as
a possible method for addressing this issue (Washida, 2005; Yuan et al., 2010).
In recognition of the value of CPFR in this domain, Panahifar et al. (2015b) found that
of the presented literature on the topic, the high-tech industry was most frequently
represented. Based on the relevance and importance of CPFR in this field this study
focuses its analytical lens on the high-tech industry and the role of retailer selection
factors in CPFR implementation.
This study focuses significantly on expert opinion and perception and the presented
methodology supports this. In particular the study includes four supporting techniques:
literature review, structural interviews, survey using fuzzy techniques and cas e study.
The general methodology and fuzzy DEMATEL workflow is outlined in Figure 1.
The labelling of Figure 1 represents the sections under which each component of the
methodology is discussed (e.g. Sections 2.1, 2.2 and 2.3). In the process of selecting and
refining retailerselection factors, the study initially utilises a literature review to develop
the CPFR retailer selection factor base which is then refined using expert opinion.
Following the refinement of the retailerselection factors, a fuzzy DEMATELapproach is
used to identify and assess the main dimensions and criteria for CPFR retailer selection.
The model and its findings were then subjected to an industrial case evaluation in a
high-tech organisation. The fuzzyDEMATEL steps used in this study are extendedfrom
(Panahifar et al., 2015c) and have been derived and updated based on approaches
presented by Lin and Wu (2008) and Chang et al. (2011). The following sections present
the main steps of the methodology, beginning with retailer selection factor identification
and refinement.
2.1 Retailer selection factor identification and refinement
To identify an initial list of retailer selection factors a detailed literature review was
completed focusing specifically on concepts relating to CPFR and collaboration partner
selection, in order to identify factors which have been identified as important
partner selection factors for CPFR implementation, and affect a partner’sability
for collaboration and information sharing with others. The keywords “CPFR”,
“collaboration”and “partner selection”in article titles were used to search the
scholarly databases of ISI Web of Science
®
, Taylor & Francis, Google Scholar™
and Emerald from the year 1998 (when CPFR was first academically documented)
up to 2014. This search resulted in the collection of 95 scholarly articles (Panahifar
et al., 2015b). These 95 articles were then critically evaluated to identify relevant
partner selection factors for collaborationingeneralandparticularlywithrespect
to CPFR implementation. This process involved two separate analytical runs for
factor analysis. In the first run, based on the key criterion of partner selection,
papers were identified and classified. In the second run, a more detailed analysis
was conducted, which involved a comprehensively assessment for each of the
selected papers for the purpose of data relevant extraction (e.g. selection factors and
dimensions).
1294
IMDS
115,7
To continue reading
Request your trial