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An investigation into critical service determinants of customer to business (C2B) type product
returns in retail firms Kamrul Ahsan and Shams Rahman
School of Business IT and Logistics, RMIT University, Melbourne, Australia
Abstract Purpose – In spite of regular occurrence of product returns, research into determinants of returns services in retail businesses is still limited. To fill the gap, the purpose of this paper is to investigate critical determinants of customer to business type product returns services in the retail industry. Design/methodology/approach – The authors develop a framework of product returns services that consists of three major service categories and 16 returns service determinants. The criticality of the determinants of product returns management are assessed employing the analytic hierarchy process (AHP) based multi-criteria decision-making approach. Under AHP set up the authors interview retail operations managers of major retail firms in Australia to identify critical determinants of product returns services. Findings – Results indicate that the most important returns services dimensions are the way in which returns services are handled through interaction, and the outcome of service delivery. The top five critical service determinants of product returns are related to: communication support service for customer, money back for any type of returns, customer support access, user-friendly interaction, and product replacement. Originality/value – The findings of the study can be considered by senior managers of retail firms as a reference guide for designing efficient and effective returns service systems and developing strategies for competitive advantage through product returns, namely, customer retention. Keywords Product returns, Analytic hierarchy process, Australian retail firms, Returns service determinants Paper type Research paper
Introduction Products returns are a reverse flow in the traditional supply chain (Rogers et al., 2002) and are categorised as activity of returning goods back through the supply chain with a focus on retailers (Bernon et al., 2011). Despite increased organisational attention to sophisticated philosophies and methods for achieving higher product quality (e.g. TQM, Six Sigma, and lean operations), volumes of returns remains high and product returns management has become one of the major challenges for retail businesses today (Petersen and Kumar, 2009).
The management of returns is a service operation involving the process of handling returned goods from customers to satisfy their needs. If the returns process is complex, slow, or inconvenient, customer dissatisfaction level escalates, which puts future business at risk (Griffis et al., 2012). Conversely, an efficient and customer focused returns operations can be a strategic asset for organisations and a source of competitive differentiation and customer-retention advantage (Petersen and Kumar, 2009). It is critical for retailers to consider returns strategically. The management of returns is becoming increasingly important as retailers see returns to maximise the value it can generate for themselves (Mollenkopf et al., 2011). As firms grow, they tend
International Journal of Physical Distribution & Logistics Management Vol. 46 No. 6/7, 2016 pp. 606-633 © Emerald Group Publishing Limited 0960-0035 DOI 10.1108/IJPDLM-09-2015-0235
Received 29 September 2015 Revised 18 November 2015 16 January 2016 Accepted 2 February 2016
The current issue and full text archive of this journal is available on Emerald Insight at: www.emeraldinsight.com/0960-0035.htm
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to handle an increased number of products, and at the same time the number of product returns also increases (Ahsan and Rahman, 2013). As a result, demand relating to product returns services increases. Some leading edge companies with increased sales and returns have realised the strategic value of returns services and emphasised on maintaining a full-time administration for the product returns process (Stock et al., 2006).
In spite of its strategic importance, research in the field of customer service determinants of product returns is limited (Mollenkopf et al., 2011; Bonifield et al., 2010). Furthermore, returns management research shows that less attention has been given to link customers with the returns policies and processes (Rogers et al., 2002; Mollenkopf et al., 2007, 2011). With the aim of extending the returns management literature, the objective of this research is to identify and prioritise critical determinants for customer to business (C2B) type product returns services in the context of Australian retail industry. We consider fairness theory (Adams, 1965) as a theoretical foundation of returns services, and develop an analytic hierarchy process (AHP) based multi- criteria returns services determinants model. By emphasising service as a critical aspect of returns management for retail firms, this research provides a theoretical basis for recapturing value from returns in the context of C2B type product returns.
The rest of the paper is structured as follows. First, under literature review we discuss the theoretical perspective of the paper and product returns service determinants in the retail industry. The next section provides an overview of AHP as a research methodology and presents results with sensitivity analysis. This is followed by a discussion of the findings and the paper concludes with theoretical and managerial contribution and future research direction.
Literature review Our research identifies and prioritises critical determinants for C2B product returns services in the context of Australian retail industry. To provide a research context to our study we first discuss C2B type of returns, examine the returns service research trends and explore returns policies, and customer services in returns. Then through an extensive literature review and applying the justice theory (Adams, 1965) we identify returns service determinants of C2B type product returns.
C2B product returns C2B returns are from end customers to retailers; where returns are products that have been returned after being opened, matched with the specification or order, or used, and for some reason the customer is not happy about the product. In other words, C2B returns are returned mainly due to buyer regret or product defect, and are normally the largest type of returns (Rogers et al., 2002). Hence, the management of C2B returns is a major concern for retailers (Posselt et al., 2008). Considering all types of retail sales in the US market, it has been reported that in 2013 the value of C2B returns exceeded $267 billion or 8.6 per cent of gross sales (The Retail Equation, 2013). Historical returns rates of different retail groups demonstrate that department stores (DS) have the highest return rates (13.7 per cent) which is followed by specialty stores (10.6 per cent), home improvement stores (9.8 per cent), discounters (7.2 per cent), and electrical stores (ES) (4.7 per cent) (Kang and Johnson, 2009). Thus, the management of C2B product returns have become an important part of today’s business and our research addresses customer product returns in the context Australian retail firms.
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Returns service research trends We conduct an extensive literature search on service issues of product returns published until 2014. Only peer reviewed English language journal articles are considered in databases used by major publishers such as Elsevier, Emerald, Springer, and Wiley. We found 68 articles related to C2B returns of which 15 are related to customer returns behaviour, and only five are customer service centric. A brief overview of customer service-related articles is shown in Table I. Out of five customer service-related articles, the study by Cassill (2013) considers returns process as an important component of customer service and suggests that the time between purchase and product return plays an important role in customer satisfaction. In their studies, Bahn and Boyd (2014) and Pei et al. (2014) investigate the impact of e-tailers returns policy on customer behaviour based on justice theory and signalling theory, whereas Bahn and Boyd (2014) identify relationship between returns policy restrictiveness and consumer evaluation of a product assortment. Smith (2005) explores customer service support for e-tailer product returns and emphasises on improving customer online shopping experience by providing customer refunds promptly. Collier and Bienstock (2006) emphasise on customer perception of quality and satisfaction on e-tailer return process, and use “fairness theory” to assess customer satisfaction. These studies on product returns service are mostly in e-tailing environment, only a limited research have been conducted in the field of returns services in retail environment, particularly in the context of identifying customer service determinants of product returns.
Customer centric research study topic Source Brief outline of study
Consumer perception and reaction on returns policy (two studies)
Pei et al. (2014) Study 1: this study investigates the effects of e-tailers returns policy on customer behaviour based on justice theory and signalling theory
Bahn and Boyd (2014)
Study 2: this research focuses on understanding the relationship between return policy restrictiveness, and consumers’ evaluations of a product assortment
Consumer satisfaction on returns process (one study)
Cassill (2013) Study 1: the focus of this study is on the return process which is an important component of customer service. Results of this study suggest that the time between purchase and returns plays an important role in the return process and is linked to customer satisfaction and dissatisfaction
Customer service provision (two studies)
Smith (2005) Study 1: through empirical analysis this study identifies easy return items have a significant positive influence on purchasing decisions. Recommendations are made for e-tailers to focus on getting refunds to customers quickly, and develop an appropriate system for quick handling of returns
Collier and Bienstock (2006)
Study 2: this research demonstrates that customer perceptions regarding quality and satisfaction of e-tailers depends upon three things: interaction with the website, delivery of the product, and how prepared retailers are to address returns problems
Table I. Overview of articles related to customer to business (C2B) returns services
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Returns policy and service issues A returns policy ensures post-purchase customer satisfaction (Bahn and Boyd, 2014) and is an element of a bundle of services with a set of restrictions imposed on consumers that may be provided by retailers (Davis et al., 1998). Restrictions include time limits for returns; return in original packaging materials; original proof of purchase (purchase receipt), no change of mind returns, and acceptance of only those products with no visible signs of use. Before making a purchasing decision, customers consider the returns policy and check whether it ensures a convenient return, hence it gives peace of mind to the customer before they buy products or services (Yalabik et al., 2005). However, the high costs of product returns handling are influencing retailers to institute policies to restrain product returns ( Janakiraman and Ordóñez, 2012). For example, the major retailer such as Costco, who previously installed a generous returns policy of indefinite return deadline, has now moved to a 90-day return policy on its computer items ( Janakiraman and Ordóñez, 2012).
When returning products, customers may have contrasting experiences that lead to different levels of satisfaction and dissatisfaction with returns (Cassill, 2013). Customer satisfaction levels and future loyalty depend upon whether customers feel that they are treated fairly by retailers during returns process (McColl-Kennedy and Sparks, 2003). On the other hand through handling returns effectively, retailers get a second chance to satisfy customers who were not happy for various reasons relating to purchases (Cassill, 2013; Wachter et al., 2012). Positive customer experiences significantly increase repeat business, and generate new customers through word of mouth recommendation (Mukhopadhyay and Setaputra, 2011). Therefore, retailers need to resolve customer dissatisfaction issues through effective returns service system ensuring timeliness and accuracy in processing returns (Mollenkopf et al., 2011).
Returns service determinants Adapting the justice theory (Adams, 1965) as theoretical framework for developing returns service categories, we consider product returns services with three service elements of justice. These are interactive fairness, procedural fairness, and outcome fairness. Details of returns service categories, sub-categories and determinants are explained below and summarised in Figure 1.
Interactive fairness concerns the manner in which the service problem is dealt with by service providers and the specific interactions between the service provider and the customer (Sparks and McColl-Kennedy, 2001). In the product returns context interactions refers to accessible facility or information for customer to locate and interact with retailers for available service support (Collier, 2006). We categorise interactive fairness of returns services into three service determinants that include support access, friendly interaction, and communication support service (see Figure 1). These are further discussed below:
(1) Support access: a support access system needs to be in place to handle returns as soon as they are received (Smith, 2005). Support access means customers should be able to easily locate the returns place and the returns contact person’s details including e-mail and phone number (Collier, 2006). During the product return, customers want the assurance of dealing with right person who would be able address the problem promptly (Collier and Bienstock, 2006). Otherwise, if a customer experiences a problem and cannot find a suitable way to contact the retailer, the company risks losing other customers through word of mouth
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from the dissatisfied customer (Collier and Bienstock, 2006). Retailers’ websites or smart phone applications can provide additional and more detailed information on returns policy and procedure which in turn may make return process more convenient. Moreover, compared to e-mail communication, live chat option with customer service representatives provide customers with real- time information access on returns (Elmorshidy, 2013; Ramanathan, 2011).
(2) User-friendly interaction: user-friendly interaction depends on how retail staff members interact with customers returning the product (Collier and Bienstock, 2009). Friendly interaction could be in the form of listening to the customer, giving time to air out their issues, and ensuring all returns issues are answered in a friendly/apologetic manner. The friendly interaction process should provide real-time advice on how to lodge a return as well as feedback on returns claims (Collier, 2006). By using live customer service technology or real-time information sharing through online chat option retailers can provide user-friendly support to customers and address the problems of product returns (Turel et al., 2013).
(3) Communication support service: an effective and efficient returns process cannot work without well-conceived communications processes (Stock et al., 2006). Communication support service means timely feedback is provided to the customer from acknowledgement of product return claim with valid proof of purchase, decision outcome of the claim, further feedback, and claims tracking, if applicable (Mollenkopf et al., 2011).
Procedural fairness refers policies, procedures, and responsiveness in the complaints process employed to resolve the service problem (Collier, 2006). Services related to the procedural fairness category include convenience for customer in returning the
Objective (Level 1)
Service category (Level 2)
Service sub-category (Level 3)
Service determinant (Level 4)
R e tu
rn s
m a n a g e m
e n t cr
iti ca
l se
rv ic
e d
e te
rm in
a n ts
Interactive fairness
Support access
Friendly interaction
Communication support service
Procedural fairness
Convenience
Return to any store
Retailer manages third-party interaction
Retailer absorbs returns logistics cost
Returns policy
Strict returns policy
Moderate returns policy
Lenient returns policy
Prompt resolution
Less gate-keeping rules for genuine returns
Skilled and trained personnel to handle returns
Dedicated returns service department
Software support to handle returns
Outcome fairness
Money back for any type of returns
Product replacement
Gift voucher or store credit
Figure 1. Returns management service categories, sub-categories and determinants
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product, consistency and flexibility in returns policy, and prompt resolution of returns claims (Mollenkopf et al., 2011; Posselt et al., 2008; Collier, 2006):
(1) Convenience: if a customer wants to return an item, there are requirements of procedure and documentation that must be met by the customer for the retailer to accept the return which generally are termed as “hassles” (Wachter et al., 2012). Convenience refers to less effort and hassle to claim for returns ( Janakiraman and Ordóñez, 2012). The service determinants under the convenience sub-category are discussed below: • Return to any store: return to any store includes being able to return the
product through multiple avenues – either by visiting a nearest store or any chain store or collection centre (Collier and Bienstock, 2006). The policy to allow customer to return the product to any store provides convenience to customer.
• Retailer manages third-party interaction: processing product returns using a third party can sometimes be a better choice when retailers lack the expertise, fall short of economies of scale, and considering the potential savings associated with evaluating returns and repackaging (Gorick, 2005). If the retailer deals with a third party for any of the returns transaction or delivery processes, for customer’s convenience it should be the retailer’s responsibility to follow up with the required third party on behalf of the customer, thereby reducing the effort required of the customer (Collier and Bienstock, 2006).
• Retailer absorbs any returns logistics costs: the returns process is an extra hassle and added cost for both the retailer and the customer. The consumer experiences transaction costs associated with effort to bring back the product such as travelling to the store or waiting in queue. For retailers costs include handling costs associated with processing the returns, putting the product back on shelf, or repackaging cost (Yalabik et al., 2005). As part of the service, some retailers offer full returns and bear all logistics costs involved and do not charge a return fee (Heiman et al., 2001).
(2) Returns policy: a good returns policy provides customers with protection, service assurance, and reduces customer risk associated with making a purchase (Yalabik et al., 2005). Returns policies vary with more to less restrictive gate- keeping rules (Foscht et al., 2013). Based on the level of restriction we classify three different types of returns policies and discuss below: • Strict policy: a returns policy with many gate-keeping rules and restrictions
is considered as a strict returns policy. Because of customer abuse of lenient returns policies (Bahn and Boyd, 2014) and due to high costs of product returns handling (Ruiz-Benítez et al., 2014), retailers are in favour of more restrictive policies ( Janakiraman and Ordóñez, 2012). However, researchers argue that a strict returns policy increases consumers’ perceptions of risk (Bahn and Boyd, 2014).
• Moderate policy: moderate returns policy is characterised by few gate- keeping rules and restrictions for valid returns (Yan, 2009). These policies identify an optimal point of leniency/restrictiveness that enables a retailer to positively impact consumer purchasing and firm performance (Kumar et al., 2008).
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• Lenient policy: a lenient or full returns policy is a generous policy characterised by almost no gate-keeping rules, allows change of mind returns, and 100 per cent guarantee of money back, and availability of exchange and merchandise (Bonifield et al., 2010; Pei et al., 2014). The lenient returns policy conveys a positive message to consumers which generally increases the consumers purchase intention (Pei et al., 2014).
(3) Prompt resolution: service recovery responsiveness relates to how effectively retailers handle returns which is measured as the amount of time customers must wait to sort out a claim (Mollenkopf et al., 2007). Unexplained, uncertain, and anxious waits may create customer dissatisfaction (Rogers et al., 2002). On the contrary, effective returns processing through timeliness and accuracy of returns handling can contribute to customers’ perception of value creation (Mollenkopf et al., 2011). Service determinants under the sub-category of prompt resolution are discussed below:
• Fewer gate-keeping rules for genuine returns: the gate could be exemplified as a valve opening for “wanted” returns and closing for “unwanted” returns (Hjort et al., 2013). Gate keeping refers to the screening of return requests and returned items and is a procedure employed to identify how, and which products enter the return stream (Mollenkopf et al., 2011). For genuine returns less gate-keeping rule will simplify the returns process and make the process faster.
• Skilled and trained personnel to handle returns: problem-solving approaches along with helpful attitudes of skilled and trained personnel to handle returns can transform the returns process into a value added activity (Mollenkopf et al., 2011). A general rule of thumb is that retail firms that perform the best job of processing returns are those with full-time employees responsible for the task (Stock et al., 2006).
• Dedicated returns service department: retailers with excellent product returns processing capabilities through a dedicated and efficient returns service department can have a potential competitive advantage through higher returns recovery rates (Stock and Mulki, 2009; Mollenkopf et al., 2011). If returns operations become more formalised through a dedicated unit, returns process becomes easier for employees to understand and execute (Autry, 2005).
• Software support to handle returns: most returns are paper-intensive and there is a need for a reverse logistics information system to handle returns (Smith, 2005). Through the use of software support returns management personnel can make quick decision on returns claims and outcomes, record the causes of returns, collect customer information, identify the manufacturer or distributor of a product, and take necessary repair or disposition decisions quickly (Smith, 2005).
Outcome fairness is considered as the extent of service coverage regarding claiming returns, and resending defective products or products that do not meet conditions of sale ( Janakiraman and Ordóñez, 2012; Mollenkopf et al., 2011). This coverage includes
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how retailers usually sort out returns claims through exchanges such as money back, product replacement, and gift voucher or store credit:
(1) Money back for any type of returns: retailers often offer money back (full or partial) guarantees for returns even if the product adequately fulfils its intended function (Davis et al., 1998). A full money-back policy can be considered a generous returns claim outcome with the promise that a return will not be questioned (Wood, 2001). Some retailers offer partial money-back options because they fear that opportunistic customers will misuse the option of a full money-back policy (Posselt et al., 2008).
(2) Product replacement: many faulty product returns claims are resolved through exchange for similar or different item or repair without cost (Cassill, 2013). Customers are provided replacement if the product has major problem which is due to manufacturer or retailer fault.
(3) Gift voucher or store credit: retailers often do not allow cash back for returns; instead provide full or partial refund through store gift vouchers, store credit, or a check issued to the customer (Wachter et al., 2012). Retailers think consumers may misuse their returns policy and instead of rejecting returns claims retailers are slightly flexible for product returns with no fault or change of mind returns or returns without original receipt (ACL, 2011).
Research methodology AHP – research method This study employs the AHP method for analysis. AHP is a multi-criteria decision- making approach that helps in breaking down a complex, unstructured problem into its components part in hierarchical structure. It facilitates decision makers to prioritise and rank alternatives through pairwise comparisons of conflicting objectives based on subjective judgements (Saaty, 1990). Our proposed returns management service framework is structured hierarchically with qualitative returns services categories, sub-categories, and service determinant that needs decision makers to assign subjective priority weights for judgements. Since AHP is capable to deal with qualitative aspects of criteria with subjective judgement (Subramanian and Ramanathan, 2012), the use of AHP as a research method is an appropriate approach for identifying critical returns service determinants in the retail sector. Schoemaker and Waid (1982) compared AHP with other utility models for determining priorities, e.g., direct trade-offs, point allocations, and unit weighting and concluded that AHP is the easiest to use and produced the most credible results.
Respondents in the study For collection and compilation of respondents’ opinions and application of the prioritisation procedure of critical returns service determinants we interview retail store senior managers from top Australian retailers. We conducted purposive sampling (Newman, 2003) that looks for retailers or cases that are “particularly information rich” in relationship to the questions under consideration (Yin, 2010). We consider 25 top ranked Australian retailers to identify critical returns service determinants. We choose these top retailers based on 2012 sales volume (Inside Retail, April/May 2012). These retailers have major market share in each retail group. For example, top DS such as Big W, Target, Kmart, Myers, David Jones, Retail Adventures together have a total market share of
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around 90 per cent, and top food and liquor stores such as Woolworths, Coles, and IGA have around 70 per cent of market share. We further group retailers according to the sub- group outlined by Australian Bureau of Statistics ANZSIC as DS group, ES group, sports and toys stores (STS) group, and other stores (OS) group retailer groups. For collection and compilation of experts’ opinions and application of the AHP prioritisation procedure we conducted face-to-face interviews. Initially, we approached 25 retailer store managers from 25 top ranked Australian retailers who have extensive experience and expertise in the area of returns management. We received confirmation of participation from 11 retail managers, whom we later e-mailed the questionnaire and organised face-to-face semi-structured interviews and collected data in AHP-based matrix format. Each interview lasted for approximately 70 minutes and the interview sessions was audio recorded and then cross-checked with the paper format of AHP questions. Respondents are senior-level managers who have requested to keep their name anonymous. A summary of the respondents experience and their roles are provided in Table II. Studies employing AHP are usually conducted with a small sample of senior executives who are knowledgeable with the issue under investigation (Shrestha et al., 2004). For example, Lam and Zhao (1998) used eight respondents for a quality-of-teaching study and Cheng and Li (2001) used nine construction experts to test comparability of critical success factors for construction partnering. Some of the recent studies employing AHP used sample sizes which varied between 3 and 11. For example, Barker and Zabinsky (2011) used three experts from three organisations to determine the best
Respondents Retail group Position, experience, and role
Respondent 1 Department stores (DS) group
Retail store manager; 5 years of experience to run day-to-day retail operations such as returns, ensuring standards for quality, customer service, and health and safety
Respondent 2 Retail operations manager; 6 years of experience in DS operations, deals with retail sales, store operations, customer service
Respondent 3 Store manager; 10 years of experience in retail operations including product returns customer service
Respondent 4 Electrical stores (ES) group
Retail store manager; 5 years of experience in organising sales, promotion, and managing customer returns
Respondent 5 Retail store manager, 8 years of experience in retail and sales management, and customer service
Respondent 6 Sports and toys stores (STS) group
Retail store manager, five years of experience in day-to-day supervision of retail outlets, including sales, staff, stock, and resources management
Respondent 7 Retail store manager and leader of the store team; 8 years of experience in customer service and people management
Respondent 8 Retail store manager; 5 years of experience in store management including customer service
Respondent 9 Other stores (OS) group
Retail store manager; 6 years of experience in customer service and sales, end-of-day reconciliation, and organisation of staff and store
Respondent 10 Retail store manager; 7 years of experience is sales and store management, and management of product returns
Respondent 11 Retail store manager; 6 years of experience in merchandising, cash handling, train and develop new and current staff, meet customer expectations
Table II. Job titles and years of experience of the participants interviewed
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network choice for product recycle collection and Subramoniam et al. (2013) used 11 responses from diverse spectrum of automotive industry. Whereas, Subramanian et al. (2014) interviewed five experts to find priorities of end-of-life product reverse logistics factors from Chinese manufacturing sector. Hence, it is evident that fewer responses from experts is the norm (Lee and Ross, 2012; Lam and Zhao, 1998) and the results of the AHP- based analysis are not influenced by a small sample size (Sambasivan and Fei, 2008).
We develop a two-part questionnaire for data collection. Part-1 is related to respondents’ opinion on relative importance of weights amongst different service categories, sub-categories and service determinants, and part-2 consists of open-ended questions about returns service issues and respondents’ background information. Under part-1, as the respondents were not familiar with AHP data collection procedure, we explained the following:
(1) concepts and basic understanding of service criteria such as service categories, sub-categories, and determinants;
(2) the meanings of the integer priority scores of the one-to-nine scale; and
(3) how the scores need to be considered while making pairwise comparisons between any two service determinants.
AHP application for determining critical service determinants With AHP, complex decision problems can be decomposed into a set of manageable decision-making problems. The process of AHP involves three steps:
Step 1 – identification of key service criteria and AHP structuring. The first step involves identification of key returns service categories, sub-categories, and determinants for the retail sector. Identification and classification of these determinants was accomplished using literature review. We consider three service categories, three sub-service categories, and 16 service determinants for product returns in the context of retail industry (see Figure 1). The structuring consists of breaking down the complex multi-criteria decision-making problem into a set of integrated levels. In this study, the problem was structured as objective, service category, service sub-category, and service determinants at four hierarchical levels.
Step 2 – pair-wise comparison of service criteria. In this step, criteria in each level are compared pair-wise in terms of their importance to a criterion in the next higher level. The scale used for pair-wise comparisons in AHP is a standard one-to-nine scale. For collection and compilation of managers’ opinions on critical returns service determinants we interview 11 retail managers and explain the AHP hierarchy structure (Figure 1). We ask respondents to judge relative importance of the three service categories and service determinants under each category and sub-category. In total seven matrices were generated: one for service categories at level 2, one for procedural service sub-categories at level 3, and five for service determinants at level 4 of the problem hierarchy.
Step 3 – determination of critical service determinants and consistency of judgements. In the third and final step of AHP, the preference matrices generated in step two are translated into largest eigenvalue problems and are solved for unique and normalised vectors of weight to criteria in each level of hierarchy. The overall weights of the service determinants are determined by aggregating the weights throughout the hierarchy.
The AHP also provides a direct measure of consistency (inconsistency) of judgment elicited by the returns service managers. The inconsistency ratio (CR) refers to the degree
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to which decision makers adhere to the rank order specified and measures the extent to which an established preference is kept. A CR ⩽ 0.1 is recommended as acceptable (Saaty and Kearns, 1985). If CRW0.1, it is suggested that the managers re-evaluate their judgments. Homogeneity of determinants/categories within each cluster of determinants, smaller number of determinants in the cluster, and better understanding of the decision problem would improve the consistency index (Saaty, 1993).
We group respondents’ judgements under the retailer category of DS Group, ES Group, STS Group, OS Group, and all four retail groups together. We calculate local priorities of service categories, sub-service categories, and service determinants and determine CR with respect to the objective and CR for each service category and sub-category. For different retail groups, details of the respondents’ judgment CR, and local priority weights of l6 service determinants are presented in Table III. For example, calculated relative priorities of returns service categories for the DS group (column 1) are weight ¼ 0.183 for interactive fairness; weight ¼ 0.322 for procedural fairness; weight ¼ 0.495 for outcome fairness and CR of judgement is 0.0007 (which is CR ⩽ 0.1 and within the acceptable limit).
We further synthesise the model with respect to the objective to determine global weights of service determinants by aggregating the weights throughout the hierarchy. Global weights of service determinants for different retail groups are shown in Table IV and Figure 2. For all retail groups CR is 0.02, which is less than the accepted limit of 0.1 and demonstrates the consistency of managers’ opinion.
Synthesising the relative priority weights of all 11 retailers, an overall ranking of three service categories is obtained. The three returns service categories are ranked as interactive fairness (weight ¼ 0.381), outcome fairness (weight ¼ 0.365), and procedural fairness (weight ¼ 0.255) (see Table III; rows 3-5). Calculations of overall CR also show that respondent’s opinions are consistent with CR¼ 0.01 (see Table IV). Similarly, synthesising the priority weights of 16 service determinants we obtain a rank order of critical service determinants. Figure 3 and Table IV (last column) reveal that the top five critical service determinants are communication support service (weight ¼ 0.185), money back for any type of returns (weight ¼ 0.177), support access (weight ¼ 0.147), user- friendly service (weight ¼ 0.110), and product replacement (weight ¼ 0.076). Results of the AHP analysis also show that the respondents’ opinions are consistent with CR ¼ 0.02.
Sensitivity analysis of the model Sensitivity analysis is one way of analysing the robustness of priority ranking (Saaty and Vargas, 2012). In AHP, the final ranking of the returns service determinants depends on the weights associated with the returns service categories such as interactive fairness, procedural fairness, and outcome fairness. Therefore, small variation in the priority in service categories could potentially change the ranking of the service determinants initially determined. Thus, sensitivity analysis is useful in providing insights due to the dynamics of returns service determinants perceptions and importance over time (Yakovleva et al., 2012):
(1) Change of weight of “interactive fairness”: we change the weight of “interactive fairness” and observe subsequent changes of priority ranks of 16 service determinants (see Figure 4). When weight of “interactive fairness” is increased from 0.381 to 0.399 (an increase of 4.7 per cent), service determinant “communication support service” becomes the third most important factor instead of “return to any store” (moves to rank 4). However, “money back for any type of returns” and
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DS group
ES group
STS group
OS group
All retail groupsReturns service category/
sub-category Service determinants Weights
CR of service categories with respect to goal
0.0007 0.0005 0.01 0.00 0.01
Interactive fairness 0.183 0.542 0.668 0.149 0.381 Procedural fairness 0.322 0.136 0.200 0.211 0.255 Outcome fairness 0.495 0.322 0.132 0.640 0.365
Interactive fairness CR with respect to “interactive fairness”
0.00 0.005 0.00 0.01 0.005
Support access 0.299 0.271 0.452 0.255 0.332 Friendly interaction 0.272 0.186 0.095 0.465 0.249 Communication support service
0.430 0.561 0.452 0.279 0.419
Procedural fairness CR with respect to “procedural fairness”
0.005 0.05 0.005 0.03 0.05
Convenience 0.417 0.076 0.241 0.516 0.356 Returns policy 0.197 0.507 0.170 0.136 0.156 Prompt resolution 0.386 0.418 0.589 0.348 0.489
Convenience CR with respect to “convenience”
0.01 0.02 0.07 0.02 0.02
Return to any store 0.544 0.327 0.169 0.673 0.436 Retailer manages third- party interaction
0.133 0.418 0.180 0.189 0.215
Retailer absorbs returns logistics cost
0.323 0.255 0.650 0.139 0.349
Returns policy CR with respect to “returns policy”
0.02 0.11 0.02 0.00 0.013
Strict returns policy 0.106 0.132 0.073 0.216 0.153 Moderate returns policy 0.545 0.638 0.393 0.506 0.503 Lenient returns policy 0.349 0.230 0.533 0.277 0.344
Prompt resolution CR with respect to “prompt resolution”
0.04 0.03 0.02 0.03 0.013
Less gate-keeping rule for genuine returns
0.201 0.057 0.113 0.160 0.129
Skilled and trained personnel
0.349 0.391 0.086 0.561 0.565
Dedicated returns service department
0.233 0.398 0.128 0.194 0.175
Software support to handle returns
0.216 0.154 0.183 0.085 0.131
Outcome fairness CR with respect to “outcome fairness”
0.003 0.07 0.05 0.011 0.052
Money back for any type of returns
0.616 0.073 0.594 0.612 0.571
Product replacement 0.173 0.735 0.249 0.255 0.243 Gift voucher/store credit 0.211 0.192 0.157 0.133 0.186
Table III. Relative weights of
returns service determinants and consistency index
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DS group
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All retail groups
Overall CR of judgement 0.01 0.02 0.02 0.02 0.02 Major returns service category/sub-category Service determinants Overall weights
Interactive fairness Support access 0.065 0.156 0.327 0.048 0.147 Friendly interaction 0.059 0.096 0.069 0.087 0.110 Communication support service
0.094 0.323 0.327 0.052 0.185
Procedural fairness Convenience Return to any store 0.069 0.005 0.006 0.064 0.044
Retailer manages third- party interaction
0.017 0.006 0.007 0.018 0.022
Retailer absorbs returns logistics cost
0.041 0.004 0.024 0.013 0.035
Returns policy Strict returns policy 0.006 0.008 0.002 0.007 0.006 Moderate returns policy 0.033 0.041 0.012 0.017 0.019 Lenient returns policy 0.021 0.015 0.017 0.009 0.013
Prompt resolution Less gate-keeping rule for genuine returns
0.037 0.005 0.011 0.012 0.014
Skilled and trained personnel
0.064 0.033 0.058 0.043 0.061
Dedicated returns service department
0.043 0.034 0.013 0.015 0.019
Software support to handle returns
0.040 0.013 0.018 0.007 0.014
Outcome fairness Money back for any type of returns
0.254 0.019 0.065 0.373 0.177
Product replacement 0.071 0.192 0.027 0.155 0.076 Gift voucher/store credit 0.087 0.050 0.017 0.081 0.058
Table IV. Overall weights and consistency index of judgements for different retail groups
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“skilled and trained personnel to handle returns” rankings remain in the top two positions. With further increase of the weight to 0.45 (18.1 per cent), “skilled and trained personnel to handle returns” position moves down to rank 3, and “communication support service” becomes the second most important factor; however “money back for any type of returns” remains at rank 1. Furthermore, with the increase of weight to 0.5, the “communication support service” moves up to rank 1 and “money back for any type of returns” down to rank 2. Further changes of the priorities to 0.6 will push down the “money back for any type of returns” to rank 4, and “user-friendly interaction” will move up to rank 3. Likewise, with a slight decrease of the weight of the “interactive fairness” from 0.381 to 0.374 (1.8 per cent), “communication support service” moves down to rank 5, and “product replacement” moves up to rank 4. Further decrease of the weight to 0.24 (37 per cent) will result in lowering the rank order of “communication support service”, “support accesses” and “user-friendly interaction” to the lowest rank orders, and there will be no further change in priorities of any determinants.
(2) Change of weight of “procedural fairness”: we further observe the sensitivity of service determinants ranks with the change of procedural fairness weight. From Figure 5, it can be observed that with the increase of the “procedural fairness” weight from 0.255 to 0.265 (an increase of 3.9 per cent), the rank between “retailers absorbs returns logistics cost” (new rank 5, previous rank 6) and “product replacement” are interchanged (new rank 6, previous rank 5), whilst the top four service determinants remain in the same rank. With further increase of weight to 0.385 (50.9 per cent), “skilled and trained personnel to handle returns” becomes rank 1 service determinant whilst “money back for any type of returns” moves down to rank 2; however rank order of “return to any store” remains the same (rank 3). This implies that retailers who focus more on “procedural fairness” of returns services need to emphasis more on “skilled and trained personnel to handle returns”. It also shows that increase of “procedural fairness” weight is sensitive to most of the initially determined top and medium ranked service determinants. On the other hand, the decrease of original weight of “procedural fairness” from 0.255 to 0.185 (27.45 per cent), changes the priority position of “returns to any store” (new rank 4, previous rank 3) and “communication”
Communication support service
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Money back for any type of returns Support access User-friendly interaction Product replacement
Gift voucher/store credit Return to any store
Retailer absorbs returns logistics cost Retailer manages third-party interaction Moderate returns policy Dedicated returns service department
Less gate-keeping rule genuine returns Software support to handle returns Lenient returns policy Strict returns policy
0.185
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Overall Inconsistency = 0.02
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Figure 3. Overall weights and rankings of returns
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(new rank 3, previous rank 4), and keeps the “money back for any type of returns” (rank 1) and “skilled and trained personnel to handle returns” (rank 2) in the same position. Analysis shows that decrease of “procedural fairness” weight is not very sensitive to most of the top and medium ranked service determinants.
(3) Change of weight of “outcome fairness”: lastly, from Figure 6 we investigate the impact of change of weights of the “outcome fairness” on initial ranking of the returns service determinants. With a slight increase of weight from 0.365 to 0.371 (1.6 per cent), critical service determinants “product replacement” moves to new rank 4 from rank 5, communication moves down to rank 5 from rank 3, whilst the top three service determinants retain their position. With further increase of weight to 0.475, “product replacement” service determinant moves up to rank 2, however initially determined top service determinant (money back for any type of product) remains in the same rank. With further increase of weight to 0.53, “gift voucher or store credit” moves up to rank 3, however there is no change in “money back for any type of product” (rank 1), “product replacement” remains in rank 2, and the seven lower ranked service determinants ranks remain unchanged. With the decrease of weight from 0.365 to 0.295, “skilled and trained personnel to handle returns” moves up to rank 1, and “money back for any type of product” moves down to rank 2, whilst “return to any store” remains in rank 3, and “communication” remains in rank 4. With further reduction of weight to 0.25, “money back for any type of product” moves down to rank 3, “returns to any store” criteria moves up to rank 2, and “communication” remains in rank 4. This analysis shows that decrease of “outcome fairness” weight is most sensitive to most of the top and medium ranked service determinants. Retailers with less priority on outcome fairness should give more emphasis on services related to convenience through returns to any store, and prompt resolution of returns claim through skilled and trained returns personnel.
Discussion of results Returns service categories and determinants The results of the analysis for all retail groups indicate that the most important return service category is “interactive fairness” with priority weight ¼ 0.381. The second most important category found is “outcome fairness” (weight ¼ 0.365) and this is followed by “procedural fairness” (weight ¼ 0.255). The overall CR ¼ 0.01 which is within the allowable limit. In order to assess whether or not any particular retail group emphasises on any specific return service category, we analyse each retail group individually. Results indicate that the ES group give more importance to interactive fairness service category (weight ¼ 0.542) and less importance to procedural fairness service category (weight ¼ 0.136). On the other hand, DS group and OS group emphasis more on the outcome fairness aspect of return service category with weights of 0.495 and 0.640, respectively. Both these groups of stores give less priority to the interactive fairness service category (weight ¼ 0.183 for DS group and weight ¼ 0.149 for OS group). Compared to OS group, priorities given by the managers of the STS group’ are more balanced with marginally more emphasis on the interactive fairness (weight ¼ 0.381) and outcome fairness (weight ¼ 0.365). A comparison of results for all four store groups reveal that the ES group give highest priority to the interactive fairness (weight ¼ 0.542) whereas, OS group gives least priority (weight ¼ 0.149). On the other hand, the most emphasis on the outcome fairness is given by OS group
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(weight ¼ 0.640), whereas the least emphasis is given ES group with weight ¼ 0.322. The importance given by the retail groups on procedural fairness are more or less uniform except for the ES group. Based on the results in Table III, we further discuss returns service categories and service determinants.
Returns services related to interactive fairness. All retailer groups together consider interactive fairness as the most important returns service category. Services literature also highlighted the general importance of interactive fairness (Sparks and McColl-Kennedy, 2001). In this study the interactive fairness is conceptualised using three returns service determinants that are support access, friendly interaction, and communication support service. It is evident from the results that all retail groups individually and jointly considered “communication” as the most critical return service determinant. The importance of communication was also highlighted during the interview by one of the ES managers (Respondent No. 5):
I think good interactive fairness is critical for our business. Because most of the time people return products because they don’t understand how to use the products or set it up. They will quite often return something that may take only 30 seconds to explain how to use or set up. We explain how to use the articles. Generally these products are not returned.
Returns services related to outcome fairness. Analysis of all retail groups combined indicates that “outcome fairness” is the second most important returns service category. However, DS group and OS group give highest priority to the “outcome fairness”. This was also revealed in the interview with one of the managers (Respondent No. 3) from the DS group:
Customers want the outcome and they aren’t really interested to know how it happens.
Another respondent (Respondent No. 10) from the OS group mentioned:
With regard to faulty product, our brands go through so much testing, but if it comes down to a question of faulty product that decision lies with me (retail floor manager). If it looks like the customers are at fault, at times we offer 50% off on a replacement item. We then take the item and return to the manufacturer even though the customer is at fault.
In this study we have operationalised the “outcome fairness” using three returns service determinants such as money back for any type of returns, product replacement, and provide gift voucher or store credit. Results indicate that the DS group and OS group consider “money back for any type of returns” as the most critical returns service determinant, whereas, the ES consider “product replacement” as the most critical determinant. An analysis with all retail groups together indicates that “money-back for any type of returns” is the most critical service determinant.
Returns services related to procedural fairness. Procedural fairness is considered to be the least important returns service category. Within the procedural fairness category, sub-categories of services are prompt resolution, convenience, and returns policy. Results regarding these sub-categories of service are discussed below.
Prompt resolution is found to be the most important sub-category of the procedural fairness service category (weight ¼ 0.489). It has been operationalized by four determinants such as less gate-keeping rule, skilled and trained personnel, dedicated returns service department, and software support. An analysis taking all retail groups together, reveals that managers consider “skilled and trained personnel” as the most critical service determinant (weight ¼ 0.565, see Table III). Literature suggests that
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skilled people are the missing link in the return management, for effective resolution of returns there is no alternative to having professionally trained people (Stock et al., 2006).
A comparison of results between the retail stores indicate that DS, and OS consider “skilled and trained personal” as the most critical service determinant; ES consider having a “dedicated returns service department” as the most important; and STS emphasise more on “software support to handle returns”. Previous studies on retail returns also support the importance of skilled, trained and full time personnel and facilities for returns handling (Stock et al., 2006).
Convenience is considered as the second most important sub-category of service under procedural fairness (weight ¼ 0.381, see Table III). All the retail groups together consider “returns to any store” as an important service determinant with weight ¼ 0.436. DS and OS consider “returns to any store” as an important service determinant, whereas ES believe “retailer managed third party interaction” is the main convenience related service determinant for returns.
Returns policy can be considered as a kind of quality assurance to the customers who are unsure about the fitness of the product prior to purchase (Bahn and Boyd, 2014). However, results revealed that retailers consider returns policy issues as least important (weight ¼ 0.156). Under the returns policy sub-category, all the retail groups together are in favour of the “moderate returns policy” related returns services. Individually, DS, ES, and OS are in also favour of institutionalising a moderate returns policy; and STS consider lenient policy an important service determinant, with none of the retail groups considering strict returns policy as a major service determinant.
Identification of critical service determinants for product returns There are 16 operational level returns service determinants in the proposed returns service model. We determine overall (global) criticality of these service determinants for different groups of retail stores individually and combined. For all retailers together, the top five critical service determinants found are communication support service, money back for any type of returns, support service, user-friendly interaction, and product replacement (see Figure 3). Whereas, the least important five service determinants are strict returns policy, lenient returns policy, software support to handle returns, less gate-keeping rule for genuine returns, and dedicated returns service department. It is important to observe that out of top five critical determinants three belong to the interactive fairness category. Hence, for designing an effective returns service system managers must emphasise on the interactive fairness service category and be flexible to give money back for any returns or replace the product depending on customers’ demand. Individually, store groups differ in their emphasis on return service determinants. For example, the top five determinants for the DS group are money back for any type of returns, communication support service, gift voucher/ store credit, product replacement, and return to any store. Whereas, the top five determinants considered by the ES group are communication support service of returns, product replacement, support access, friendly interaction, and moderate return policy. Therefore, it is evident that for effective design and development of a returns system, management of the DS group is required to emphasise mainly on the “outcome fairness” category and be flexible in allowing customer to return products to any store and willing to replace product if necessary. For designing an appropriate return service system, the ES group on the other hand, should emphasise exclusively on the “interactive fairness” category with willingness to replace products adopting a
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moderate returns policy. Top five determinants considered by the STS group are support access, communication support service, friendly interaction, money back for any type of returns, and skilled and trained personnel. This means, in order to design and implement an efficient returns system, management of the STS group must emphasise exclusively on the “interactive fairness” category and provide guarantee for money back for any type of returns delivered by skilled and trained staff. The OS group identified money back for any type of returns, product replacement, friendly interaction, gift voucher/store credit, return to any store as the top five critical determinants. Hence, for the OS group the most effective returns service system will be the one which will deliver service in a friendly environment focusing mainly on the “outcome fairness” service category and allowing customers to return their product to any store. It is therefore evident that to design and implement an efficient returns system in C2B type product returns the DS group and OS group must emphasise on the “outcome fairness” service category, whereas, the ES group and STS group must concentre mainly on the “interactive fairness” service category. The design elements of different retail stores groups is summarised in Table V.
The importance of interaction and communication channel throughout the returns process is considered a critical aspect of effective return management (Stock et al., 2006; Collier, 2006). At the first stage of returns, customers seek an access point to claim product returns. During this step, customers should be provided with easy access and user-friendly service to find the returns service desk, telephone number, e-mail address
Retail group Top 5 service determinants Retail returns service design elements for C2B type returns
DS group Money back for any type of returns Communication support service Gift voucher/store credit Product replacement Return to any store
For effective design and develop of a returns system, management is required to emphasise mainly on the “outcome fairness” category and be flexible in allowing customer to return products to any store and willing to replace product if necessary
ES group Communication support service Product replacement Support access Friendly interaction Moderate returns policy
The most appropriate returns system should emphasise exclusively on the “interactive fairness” category with willingness to replace products adopting a moderate returns policy
STS group Communication support service Support access Friendly interaction Money back for any type of returns Skilled and trained personnel
To design and implement an efficient returns system, management must emphasise exclusively on the “interactive fairness” category and must provide guarantee for money back for any type of returns delivered by skilled and trained staff
OS group Money back for any type of returns Product replacement Friendly interaction Gift voucher/store credit Return to any store
The most effective returns service system will be the one which will deliver service in a friendly environment focusing mainly on the “outcome fairness” service category and allowing customers to return their product to any store
Table V. Retail returns service design elements for C2B type returns
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of customer service. Afterwards, retailers interact with customer where customers explain the causes of service failure and claim product replacement, repair or money back. An efficient communications support service is necessary to provide acknowledgement of returns claim, decision outcome and claim tracking or feedback. Since it is a service recovery opportunity, retailers should provide proper customer support and ensure a positive experience. Uncertain and anxious waits for returns may create customer frustration and may be perceived as ceremonial with a lack of communication fairness (Rogers et al., 2002). Moreover, to ensure a positive customer experience friendly interaction with customers is important in returns situations (Ulaga, 2003). Positive customer experiences significantly increase repeat business and generate new customers through word of mouth recommendation (Mollenkopf et al., 2011). Among the retailer groups, the ES group emphasise more on communication support service. Most of the products handled in the electrical category are technology related and about 50 per cent of the product returns in consumer electrical are not due to product defect, but due to customer difficulty in properly operating the product (Rogers et al., 2002). In such case communication support is critical.
The highest emphasis given by the DS group and OS group is on the money back for any type of returns determinant. Studies show that customers return products mainly because of change of mind and product quality issues (Autry, 2005) and in both cases customers expect the outcome to be money back. A money back guarantee signals seller confidence in the quality of their product (Shen et al., 2011). Full money-back options are valuable to consumers because they reduce the purchase risk of quality product (McWilliams, 2012) and offering full money back can help increase retailers’ profitability (Davis et al., 1998). This study finds that the ES group give less importance to money back and prefer to replace the product due to quality issues regarding the product. This is due to the nature of products they sell to customer with moderate returns policy.
Besides the top five critical service determinants, “skilled and trained personnel to handle returns” is the only determinant (rank 6) that falls under the sub-category “prompt resolution”. Prompt resolution of returns through skilled personnel is a key component of overall returns experience (Griffis et al., 2012), unfortunately many retailers often reluctant to spend time and resources on returns because such activities take away from the main selling objectives (Mollenkopf et al., 2011). Yet another important service determinant is related to conveninece of returns service. Retailers prefer to provide returns convenience through the option of flexible returns location (rank 8), and absorbing extra cost of returns logistics (rank 9). Sensitivity analysis shows that the change of interactive fairness weight (range: 0.240-0.600) and outcome fairness weights (from 0.375 to 0.475) have impact on change of weights of other critical service determinants. This means decision makers need to prioritise new service determinants with the change of priorities of these two service categories.
Research implications Our research contributes to the reverse logistics literature by determining critical C2B returns service determinants for the Australian retail sector. Here we highlight both theoretical and practical implications of this study.
Theoretical implications Generally, organisations view returns as a non-value adding function, and hence pay less attention to the opportunities that effective returns management can deliver
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(Bernon et al., 2011; Stock et al., 2006). Emphasising that the service is an important aspect of returns management for retail firms, our research provides a theoretical basis for recapturing value from returns by focusing on interactive and outcome fairness categories of returns service.
Our research, irrespective of product type, identifies that retailers judge the “communication support service” and the manner in which “outcome of product returns claims are handled” as the two most important returns service determinants. All retailers individually and jointly deem the communication support service as the most critical determinant of returns service. During returning products, customers want the assurance of discussing their concerns with the service providers to ensure that their issues are being appropriately and promptly addressed. Maintaining timely interaction and communication throughout the returns process is considered a critical aspect of effective return management. Through proper interaction with the customer, retailers can come to recognise the root causes of return and other related returns issues which could be solved promptly for customer retention. Retaining customers is the most significant challenge for Australia’s retailers with a recent survey showing 22 per cent of retailers identify this as the number one challenge of 2015 (Frost and Sullivan, 2015). Hence, communication support is a prime opportunity for retailers to recapture their customers.
This research also finds outcome of returns such as full money back and product replacement as two other critical determinants of returns services that retailers must emphasise upon to resolve customer returns. A product returns claim is considered complete once the retailer has received the returned merchandise and authorised or processed a refund to the customer (Griffis et al., 2012). On the one hand, the returns policies with full money back and product replacement provides customers a peace of mind before they purchase a product and signals seller confidence in the quality of their product.
Outcome options of full money back and product replacement are also a point of comparison with other retailers. Therefore, although liberal policies cost more for companies, liberal returns policies convey a positive message to consumers, that generally strengthens the consumers purchase intention and hence increases sales or has positive impact on company’s bottom line (Pei et al., 2014). The issue of skilled manpower is another important determinant of returns service. A general rule of thumb is that retail firms that perform the best job of processing returns are those with full-time employees responsible for the task (Stock et al., 2006). Skilled personal with a problem-solving attitude for service recovery can provide positive customer experiences to increase repeat business and generate new customer, hence translate returns into a more value added activity through more sales (Autry et al., 2007; Mollenkopf et al., 2011).
Managerial implications The most important managerial contribution of our research is to suggest efficient and effective design elements of retail return services in the retail business context. This study indicates that not all service determinants are equally important for designing efficient returns services. Based on the level of importance, we isolate the most critical determinants from the least critical ones. For designing an effective returns service system retail managers must emphasise on the interactive returns service and related logistics issues and be flexible to provide money back for any returns or replace the product depending on customers’ demand. For example, determinants such as communication support service, skilled and trained personnel, user-friendly interaction, money back or product replacement are more critical compared to retailer absorbing return costs or dedicated return service department. Given the fact that businesses
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operate under severe resource constraints addressing the vital few determinants in providing returns services makes retailers more efficient and effective.
Being mindful of the fact that all retailers’ service elements may not the same; we investigate the returns services requirement for each category of retailer separately. Based on the findings, this study develops a retail returns service design guidelines for C2B type returns for different group of retailers. Having a returns service design guideline help retailers assessing their current returns service practices, understand how the policies are implemented across the retail groups and evaluate how returns management can be made more value adding. For example, for designing an efficient and effective returns service system of ES, and STS emphasis must be given exclusively on the “interactive fairness” category with willingness to replace products adopting a moderate returns policy or provide guarantee for money back for returns. For effective design and develop of a returns system of the DS and OS, management is required to emphasise mainly on the “outcome fairness” category and be flexible in allowing customer to return products to any store and willing to replace product if necessary.
Conclusions and limitation With the aim of extending the returns management literature we develop a framework of product returns services and critical determinants for C2B type returns services in the context of the retail industry. We consider the fairness theory (Adams, 1965) as a theoretical foundation of returns services and develop an AHP-based multi-criteria returns services determinants framework. The framework consists of three major service categories and 16 returns service determinants; which is developed based on extensive literature review in the areas of marketing, logistics and service management. To the best of our knowledge, no previous research has attempted to develop this unique C2B type returns service framework with determinants to extend the current reverse logistics literature in the returns management area. This study reveals that the top five critical service determinants of product returns are related to communication support service for customer, money back for any type of returns, customer support access, user-friendly interaction, and product replacement. The least important five service determinants are strict returns policy, lenient returns policy, software support to handle returns, less gate- keeping rule for genuine returns, and dedicated returns service department.
Sensitivity analyses show that ranking of critical service determinants are sensitive to slight changes (increase or decrease) of interactive fairness and outcome fairness weights. This would help managers to develop alternative strategies through “what if?” type scenario analysis. Moreover, our research suggests a returns service design guideline for four different types of retail groups which could act as a reference to retail managers for designing efficient and effective returns service and related logistics, and developing strategies for competitive advantage, namely, customer retention and asset management.
Given the nature of our problem we employ AHP as the method for analysis. As a method AHP is theoretically sound and widely accepted for prioritising the alternatives based on hard-to-quantify and qualitative criteria. However, while evaluating the criticality of different criteria, AHP does not take into account the relationships among the criteria being used. In many situations, relationships among the criteria may exist and hence, an evaluation based on the potential relationships may provide a more realistic assessment of the situation (Yakovleva et al., 2012). Future research may consider this issue by employing either analytic network process or any other suitable methodology.
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References
ACL (2011), “The Australian Consumer Law (ACL)”, ACT 2600, Commonwealth of Australia 2010, Canberra.
Adams, J.S. (1965), “Inequity in social exchange”, Advances in Experimental Social Psychology, Vol. 2, pp. 267-299.
Ahsan, K. and Rahman, S. (2013), “Management of product returns in retail firms: an investigation into critical determinants”, in Grimmer, M. and Rob, H. (Eds), The 27th Australian and New Zealand Academy of Management Conference 2013: Managing on the Edge, Australian and New Zealand Academy of Management, Hobart, pp. 1-15.
Autry, C.W. (2005), “Formalization of reverse logistics programs: a strategy for managing liberalized returns”, Industrial Marketing Management, Vol. 34 No. 7, pp. 749-757.
Autry, C.W., Hill, D.J. and O’Brien, M. (2007), “Attitude toward the customer: a study of product returns episodes”, Journal of Managerial Issues, Vol. 19 No. 3, pp. 315-339.
Bahn, K.D. and Boyd, E. (2014), “Information and its impact on consumers’ reactions to restrictive return policies”, Journal of Retailing and Consumer Services, Vol. 21 No. 4, pp. 415-423.
Barker, T.J. and Zabinsky, Z.B. (2011), “A multicriteria decision making model for reverse logistics using analytical hierarchy process”, Omega, Vol. 39 No. 5, pp. 558-573.
Bernon, M., Rossi, S. and Cullen, J. (2011), “Retail reverse logistics: a call and grounding framework for research”, International Journal of Physical Distribution & Logistics Management, Vol. 41 No. 5, pp. 484-510.
Bonifield, C., Cole, C. and Schultz, R.L. (2010), “Product returns on the internet: a case of mixed signals?”, Journal of Business Research, Vol. 63 Nos 9-10, pp. 1058-1065.
Cassill, N.L. (2013), “Do customer returns enhance product and shopping experience satisfaction?”, The International Review of Retail, Distribution and Consumer Research, Vol. 8 No. 1, pp. 1-13.
Cheng, E.W.L. and Li, H. (2001), “Information priority‐setting for better resource allocation using analytic hierarchy process (AHP)”, Information Management & Computer Security, Vol. 9 No. 2, pp. 61-70.
Collier, J.E. (2006), “Measuring service quality in e-retailing”, Journal of Service Research, Vol. 8 No. 3, pp. 260-275.
Collier, J.E. and Bienstock, C.C. (2006), “How do customers judge quality in an e-tailer?”, MIT Sloan Management Review, Vol. 48 No. 1, pp. 35-40.
Collier, J.E. and Bienstock, C.C. (2009), “Model misspecification: contrasting formative and reflective indicators for a model of e-service quality”, The Journal of Marketing Theory and Practice, Vol. 17 No. 3, pp. 283-293.
Davis, S., Hagerty, M. and Gerstner, E. (1998), “Return policies and the optimal level of ‘hassle’ ”, Journal of Economics and Business, Vol. 50 No. 5, pp. 445-460.
Elmorshidy, A. (2013), “Applying the technology acceptance and service quality models to live customer support chat for e-commerce websites”, Journal of Applied Business Research, Vol. 29 No. 2, pp. 589-596.
Foscht, T., Ernstreiter, K., Maloles, C. III, Sinha, I. and Swoboda, B. (2013), “Retaining or returning?: some insights for a better understanding of return behaviour”, International Journal of Retail & Distribution Management, Vol. 41 No. 2, pp. 113-134.
Frost and Sullivan (2015), The Customer Experience Challenges for Australian Retailers, Australian Retailers Association (ARA), Melbourne.
Gorick, J. (2005), “Reverse logistics”, Soap, Perfumery & Cosmetics, Vol. 78 No. 6, p. 17.
630
IJPDLM 46,6/7
Griffis, S.E., Rao, S., Goldsby, T.J. and Niranjan, T.T. (2012), “The customer consequences of returns in online retailing: an empirical analysis”, Journal of Operations Management, Vol. 30 No. 4, pp. 282-294.
Heiman, A., McWilliams, B. and Zilberman, D. (2001), “Demonstrations and money-back guarantees: market mechanisms to reduce uncertainty”, Journal of Business Research, Vol. 54 No. 1, pp. 71-84.
Hjort, K., Lantz, B., Ericsson, D. and Gattorna, J. (2013), “Customer segmentation based on buying and returning behaviour”, International Journal of Physical Distribution & Logistics Management, Vol. 43 No. 10, pp. 852-865.
Janakiraman, N. and Ordóñez, L. (2012), “Effect of effort and deadlines on consumer product returns”, Journal of Consumer Psychology, Vol. 22 No. 2, pp. 260-271.
Kang, M. and Johnson, K. (2009), “Identifying characteristics of consumers who frequently return apparel”, Journal of Fashion Marketing and Management, Vol. 13 No. 1, pp. 37-48.
Kumar, V., George, M. and Pancras, J. (2008), “Cross-buying in retailing: drivers and consequences”, Journal of Retailing, Vol. 84 No. 1, pp. 15-27.
Lam, K. and Zhao, X. (1998), “An application of quality function deployment to improve the quality of teaching”, International Journal of Quality & Reliability Management, Vol. 15 No. 4, pp. 389-413.
Lee, S. and Ross, S.D. (2012), “Sport sponsorship decision making in a global market”, Sport, Business and Management: An International Journal, Vol. 2 No. 2, pp. 156-168.
McColl-Kennedy, J.R. and Sparks, B.A. (2003), “Application of fairness theory to service failures and service recovery”, Journal of Service Research, Vol. 5 No. 3, pp. 251-266.
McWilliams, B. (2012), “Money-back guarantees: helping the low-quality retailer”, Management Science, Vol. 58 No. 8, pp. 1521-1524.
Mollenkopf, D.A., Frankel, R. and Russo, I. (2011), “Creating value through returns management: exploring the marketing-operations interface”, Journal of Operations Management, Vol. 29 No. 5, pp. 391-403.
Mollenkopf, D.A., Rabinovich, E., Laseter, T.M. and Boyer, K.K. (2007), “Managing internet product returns: a focus on effective service operations”, Decision Sciences, Vol. 38 No. 2, pp. 215-250.
Mukhopadhyay, S.K. and Setaputra, R. (2011), “Return policy in product reuse under uncertainty”, International Journal of Production Research, Vol. 49 No. 17, pp. 5317-5332.
Newman, M.E. (2003), “Ego-centered networks and the ripple effect”, Social Networks, Vol. 25 No. 1, pp. 83-95.
Pei, Z., Paswan, A. and Yan, R. (2014), “E-tailer’s return policy, consumer’s perception of return policy fairness and purchase intention”, Journal of Retailing and Consumer Services, Vol. 21 No. 3, pp. 249-257.
Petersen, J.A. and Kumar, V. (2009), “Are product returns a necessary evil? Antecedents and consequences”, Journal of Marketing, Vol. 73 No. 3, pp. 35-51.
Posselt, T., Gerstner, E. and Radic, D. (2008), “Rating e-tailers’ money-back guarantees”, Journal of Service Research, Vol. 10 No. 3, pp. 207-219.
Ramanathan, R. (2011), “An empirical analysis on the influence of risk on relationships between handling of product returns and customer loyalty in e-commerce”, International Journal of Production Economics, Vol. 130 No. 2, pp. 255-261.
631
Critical service determinants
of C2B
Rogers, D.S., Lambert, D.M., Croxton, K.L. and García-Dastugue, S.J. (2002), “The returns management process”, International Journal of Logistics Management, Vol. 13 No. 2, pp. 1-18.
Ruiz-Benítez, R., Ketzenberg, M. and van der Laan, E.A. (2014), “Managing consumer returns in high clockspeed industries”, Omega, Vol. 43, March, pp. 54-63.
Saaty, T.L. (1990), “An exposition of the AHP in reply to the paper ‘remarks on the analytic hierarchy process’ ”, Management Science, Vol. 36 No. 3, pp. 259-268.
Saaty, T.L. (1993), “What is relative measurement? The ratio scale phantom”, Mathematical and Computer Modelling, Vol. 17 No. 4, pp. 1-12.
Saaty, T.L. and Kearns, K.P. (1985), Analytical Planning: The Organization of Systems, Pergamon Press, Oxford.
Saaty, T.L. and Vargas, L.G. (2012), “How to make a decision”, in Saaty, T.L. and Vargas, L.G. (Eds), Models, Methods, Concepts & Applications of the Analytic Hierarchy Process, Springer, New York, NY, pp. 1-21.
Sambasivan, M. and Fei, N.Y. (2008), “Evaluation of critical success factors of implementation of ISO 14001 using analytic hierarchy process (AHP): a case study from Malaysia”, Journal of Cleaner Production, Vol. 16 No. 13, pp. 1424-1433.
Schoemaker, P.J. and Waid, C.C. (1982), “An experimental comparison of different approaches to determining weights in additive utility models”, Management Science, Vol. 28 No. 2, pp. 182-196.
Shen, C.-C., Chiou, J.-S. and Kuo, B.-S. (2011), “Remedies for information asymmetry in online transaction: an investigation into the impact of web page signals on auction outcome”, Internet Research, Vol. 21 No. 2, pp. 154-170.
Shrestha, R.K., Alavalapati, J.R. and Kalmbacher, R.S. (2004), “Exploring the potential for silvopasture adoption in south-central Florida: an application of SWOT-AHP method”, Agricultural Systems, Vol. 81 No. 3, pp. 185-199.
Smith, A.D. (2005), “Reverse logistics programs: gauging their effects on CRM and online behavior”, VINE: The Journal of Information and Knowledge Management Systems, Vol. 35 No. 3, pp. 166-181.
Sparks, B.A. and McColl-Kennedy, J.R. (2001), “Justice strategy options for increased customer satisfaction in a services recovery setting”, Journal of Business Research, Vol. 54 No. 3, pp. 209-218.
Stock, J., Speh, T. and Shear, H. (2006), “Managing product returns for competitive advantage”, MIT Sloan Management Review, Vol. 48 No. 1, pp. 57-62.
Stock, J.R. and Mulki, J.P. (2009), “Product returns processing: an examination of practices of manufacturers, wholesalers/distributors, and retailers”, Journal of Business Logistics, Vol. 30 No. 1, pp. 33-62.
Subramanian, N. and Ramanathan, R. (2012), “A review of applications of analytic hierarchy process in operations management”, International Journal of Production Economics, Vol. 138 No. 2, pp. 215-241.
Subramanian, N., Gunasekaran, A., Abdulrahman, M. and Liu, C. (2014), “Factors for implementing end-of-life product reverse logistics in the Chinese manufacturing sector”, International Journal of Sustainable Development & World Ecology, Vol. 21 No. 3, pp. 235-245.
Subramoniam, R., Huisingh, D., Chinnam, R.B. and Subramoniam, S. (2013), “Remanufacturing decision-making framework (RDMF): research validation using the analytical hierarchical process”, Journal of Cleaner Production, Vol. 40, February, pp. 212-220.
The Retail Equation (2013), “Consumer returns in the retail industry”, available at: www. theretailequation.com/ (accessed 24 May 2014).
632
IJPDLM 46,6/7
Turel, O., Connelly, C.E. and Fisk, G.M. (2013), “Service with an e-smile: employee authenticity and customer use of web-based support services”, Information & Management, Vol. 50 No. 2, pp. 98-104.
Ulaga, W. (2003), “Capturing value creation in business relationships: a customer perspective”, Industrial Marketing Management, Vol. 32 No. 8, pp. 677-693.
Wachter, K., Vitell, S.J., Shelton, R.K. and Park, K. (2012), “Exploring consumer orientation toward returns: unethical dimensions”, Business Ethics: A European Review, Vol. 21 No. 1, pp. 115-128.
Wood, S.L. (2001), “Remote purchase environments: the influence of return policy leniency on two-stage decision processes”, Journal of Marketing Research, Vol. 38 No. 2, pp. 157-169.
Yakovleva, N., Sarkis, J. and Sloan, T. (2012), “Sustainable benchmarking of supply chains: the case of the food industry”, International Journal of Production Research, Vol. 50 No. 5, pp. 1297-1317.
Yalabik, B., Petruzzi, N.C. and Chhajed, D. (2005), “An integrated product returns model with logistics and marketing coordination”, European Journal of Operational Research, Vol. 161 No. 1, pp. 162-182.
Yan, R. (2009), “Product categories, returns policy and pricing strategy for e-marketers”, Journal of Product & Brand Management, Vol. 18 No. 6, pp. 452-460.
Yin, R.K. (2010), Qualitative Research from Start to Finish, Guilford Press, New York, NY.
Further reading Shear, H., Speh, T. and Stock, J. (2002), “Many happy (product) returns”, Harvard Business
Review, Vol. 80 No. 7, pp. 16-17.
Corresponding author Shams Rahman can be contacted at: shams.rahman@rmit.edu.au
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