Increasing the consumer-perceived benefits of a mass-customization experience through sales-configurator capabilities

Computers in Industry 65 (2014) 693–705

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Computers in Industry journal homepage: www.elsevier.com/locate/compind

Increasing the consumer-perceived benefits of a mass-customization experience through sales-configurator capabilities Alessio Trentin a,*, Elisa Perin b, Cipriano Forza a a b

Universita` di Padova, Dipartimento di Tecnica e Gestione dei sistemi ind.li, Stradella S. Nicola 3, 36100 Vicenza, Italy PricewaterhouseCoopers Advisory SpA, Via Vicenza 4, 35138 Padova, Italy

A R T I C L E I N F O

A B S T R A C T

Article history: Received 4 September 2013 Received in revised form 27 November 2013 Accepted 6 February 2014 Available online 2 March 2014

The consumer’s experience of self-customizing a product with a sales configurator can be a source of experience-related benefits for the consumer, above and beyond the traditionally considered utility of possessing a product that better fits his/her idiosyncratic needs. Although such experience-related benefits have been found by previous studies as increasing consumers’ willingness to pay for masscustomized products, research on what characteristics sales configurators should have to increase such benefits is still in its infancy. In this paper, we argue that two such benefits (i.e., hedonic and creativeachievement benefits) increase as a sales configurator deploys, to a greater extent, the following capabilities: focused navigation, flexible navigation, user-friendly product space description, easy comparison and benefit-cost communication. Subsequently, by analyzing 675 self-customization experiences made by 75 engineering students on 30 real Web-based configurators of consumer goods, we find empirical support for all the hypothesized relationships. We conclude discussing the contribution of the study to relevant debates, its managerial implications as well as its limitations and the related opportunities for further research. ß 2014 Elsevier B.V. All rights reserved.

Keywords: Mass customization toolkits Product configuration Product self-customization Consumer value

1. Introduction Due to increasingly sophisticated customers and, at the same time, intensifying competition, companies are paying a growing attention to mass customization [1,2], with many successful implementation cases reported in literature [3]. While more ‘‘visionary’’ definitions of mass customization have appeared in literature since the term was coined in the late 1980s [3,4], the concept is commonly defined as the dual ability (i) to provide products and services with enough variety and customization that nearly every customer finds exactly what he/she wants and, at the same time, (ii) to avoid substantial trade-offs in cost, delivery and quality [1,5–7]. In this more ‘‘practical’’ view of mass customization [3,4], some compromise, limitations and constraints are inevitable if product customization is to be combined with the operational-performance advantages of mass production [8]. Rather than by the use of a particular technology or product mix, mass customization ‘‘is characterized by focus on customer needs’’ ([3], p. 16). First, a manufacturer pursuing mass customization needs to understand the product attributes along which its target

* Corresponding author. Tel.: +39 0444 998742; fax: +39 0444 998884. E-mail addresses: [email protected] (A. Trentin), [email protected] (E. Perin), [email protected] (C. Forza). http://dx.doi.org/10.1016/j.compind.2014.02.004 0166-3615/ß 2014 Elsevier B.V. All rights reserved.

customers’ needs diverge, as well as the different levels required by its target market for each of those attributes and the corresponding market potentials [3,4,9]. Subsequently, the manufacturer needs to define the attribute levels it is willing to offer and needs to present them to its potential customers [3,4,9]. Finally, it needs to collect each customer’s choices and translate them into manufacturing instructions [3,4,9]. All these activities necessitate intense customer–manufacturer interaction [3] and, in this interaction, an increasingly important role is played by sales configurators [3]. Sales configurators are software applications that support customers, or salespeople interacting with customers, in completely and correctly specifying a product solution within a company’s product offer [9,10]. In particular, with the advent of the Internet, many companies pursuing mass customization have started to use Web-based sales configurators that enable customers to selfcustomize their own product solutions online [3,11]. The tight linkage existing between mass customization and sales configurators is further evidenced by the fact that the customer’s experience of self-customizing a product with a sales configurator has been referred to by Merle et al. [12] as mass-customization experience. From the manufacturer’s perspective, the value of mass customization depends on various factors, including the maximum price that potential customers are willing to pay for masscustomized products [3,13,14]. In turn, willingness to pay [15] for

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mass-customized products depends on the value implications of mass customization to individual customers [14]. While the earlier literature emphasized the utilitarian benefit of possessing a product that better fits one’s idiosyncratic needs, the recent literature has developed more sophisticated knowledge of the value implications of mass customization to individual customers [3]. In particular, it has recently been acknowledged that, in addition to the benefits deriving from the possession of a masscustomized product, a consumer can also enjoy benefits resulting from the experience of self-customizing such a product with a sales configurator [12,16]. Increasing the benefits deriving from a masscustomization experience is, therefore, one key in augmenting the consumer’s willingness to pay and, ultimately, the value of mass customization on the manufacturer’s side. Limited research, however, has been devoted to the question of how sales configurators should be designed to increase the consumerperceived benefits of mass-customization experiences [11,14,17]. The present paper aims to narrow this research gap by considering two mass-customization experience-related benefits that are grounded in consumer research: namely, hedonic and creative-achievement benefits. Consistent with the theoretical grounding of these constructs, we pursue the objective of the paper with a focus on consumer goods. First, we develop hypotheses concerning how hedonic and creative-achievement benefits are influenced by five sales-configurator capabilities that have recently been defined in literature: namely, focused navigation, flexible navigation, user-friendly product space description, easy comparison and benefit-cost communication. Subsequently, we test the hypothesized positive relationships and find empirical support for all of them by analyzing 675 mass-customization experiences made by 75 engineering students on 30 real Webbased configurators of consumer goods. The remainder of the paper is organized as follows. Section 2 reviews the relevant literature. Section 3 develops the research hypotheses. Sections 4 and 5, respectively, present the method and results of the hypothesis-testing portion of the study. Section 6, finally, discusses the theoretical and managerial implications of the present work as well as its limitations and associated directions for future research. 2. Literature review 2.1. Sales configurators Since the 1980s, an increasing number of studies have dealt with sales configurators, also known in literature by other terms [11,18], such as choice boards/menus [19,20], user toolkits for innovation and design [21,22] and mass customization toolkits [11], to name but a few. Based on previous research [9,10,23], we define sales configurators as knowledge-based software applications that support a potential customer, or a sales-person interacting with the customer, in completely and correctly specifying a product solution within a company’s product offer. A fundamental function of a sales configurator is to present the options that are available within a company’s product offer [18,19], also known as product space [24] or solution space [25]. Usually, the product space modeled within a sales configurator is fully predefined, but sales configurators can also be adopted for products that still involve some custom design [10]. In addition to presenting a company’s product space, a sales configurator lets the user browse that space and specify, within it, the solution that is most appropriate to the customer’s needs [9,19]. At the same time, the sales configurator ensures that the solution specified by the user is complete (i.e., all the necessary product features have been specified) and valid (i.e., no unfeasible or inconsistent product features have been specified) [9,10,18]. To help identify the

solution that best fits the customer’s needs, the sales configurator can also provide the user with real-time feedback about the specified solution [18], such as drawings, photos, animation or other simulations of the real product on a computer, price information, and delivery terms [18,26,27]. Sales configurators are not necessarily stand-alone software applications, but may be modules of other applications, usually called product configurators, which are increasingly offered nowadays as an add-on to enterprise resource planning systems [28]. Product configurators support not only the creation of sales specifications, but also the creation of technical specifications, such as bills of materials, production sequences or technical drawings, which are necessary to build the product solution requested by a customer [10,29]. Indeed, the integration of all configuration activities, from sales specification up to production and outbound logistics, has recently been advocated as one key in achieving mass customization, and enabling approaches, models and tools have accordingly been proposed [30–32]. Many available studies in literature provide insight into relevant technical or application development issues for sales configurators (e.g., [30,33–42]). At the same time, numerous studies also shed light on the benefits and challenges of implementing and using sales configurators (e.g., [23,43–51]). A review of the results of these studies is beyond the scope of the present paper and we refer the interested reader to Heiskala et al. [10] and Falkner et al. [52] for further information. More relevant to the present paper is the review of another, relatively less-developed research stream [10,14,53,54], which addresses the question of how sales configurators should be designed to increase their benefits and overcome or alleviate the related challenges. A number of empirically tested recommendations come from experimental studies focusing on one or a limited number of sales-configurator characteristics. Huffman and Kahn [55], Kamis et al. [17] and Valenzuela et al. [54] recommend an attribute-based, rather than alternative-based, presentation of a company’s product space. This means that customers should be asked what level they prefer within each attribute of the product, rather than having to choose among fully specified product alternatives. This recommendation particularly applies to the cases in which the number of product alternatives is high [17], provided that trade-offs among attractive attributes are not made explicitly known [54,55]. Randall et al. [56] suggest that the product attributes presented to a potential customer should be product functions and product performance characteristics if the customer is inexperienced with the product, whereas they should be design parameters, such as specifications of product components, if the customer is an expert. Dellaert and Stremersch [57] recommend pricing at full-configuration level, rather than at the level of individual options. Chang and Chen [58] suggest that, depending on the type of product (search products vs. experience products), potential customers should be given different types of prepurchase information (intrinsic cues reflecting objective characteristics of the product vs. extrinsic cues such as expert reviews and word of mouth). Chang et al. [59], finally, recommend that potential customers should be provided with examples of configured products, in order to offer guidance about what to do. At the same time, such examples should be realistically achievable and not exceed the customers’ abilities of performing the self-customization task [59]. A broader set of recommendations comes from a few conceptual papers [21,26,60–63], including tailoring the mass-customization experience according to the customer’s expertise with the product, providing an initial configuration that the customer can subsequently alter, and communicating the benefits and costs of the configuration choices made by the customer. To advance theory testing on the effectiveness of these recommendations, Trentin et al.

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[64] conceptualize five sales-configurator capabilities rooted in many of these recommendations and develop and validate multiitem measurement scales for such capabilities. Finally, a few empirical studies, though not addressing the question of how sales configurators should be designed, nonetheless offer relevant suggestions in the form of managerial implications and/or further research directions [11,14,65–67]. For example, Moreau et al. [66] suggest that a mass-customization experience should be tailored to the purpose of the customer’s visit: namely, purchase for others vs. purchase for oneself. Underlying most of the above-mentioned recommendations is one or both of the following objectives [11,64]: (i) increasing the perceived preference fit of the configured product, that is the customer’s subjective evaluation of the extent to which the configured product fits his/her needs and (ii) alleviating the difficulty experienced by the customer in self-customizing a product and making a purchase decision, including both computational and non-computational sources of decision difficulty [68]. Most of these studies, in other terms, focus on the customer’s benefit of possessing a product that better fits his/her idiosyncratic needs and on the customer’s costs represented both by the time and cognitive effort invested in the mass-customization experience and by any negative emotions elicited by such an experience. This means that the mass-customization experience is often implicitly regarded merely as a source of costs for the customer (in terms of time spent, cognitive effort required and possible unpleasant emotional outcomes), which negatively impact his/ her willingness to use a sales configurator as well as the likelihood that he/she completes the self-customization task and makes a purchase [11]. The mass-customization experience, however, can also be a source of benefits for the customer, above and beyond those deriving from the possession of a mass-customized product, as discussed at length in the following subsection. How to design sales configurators to increase such benefits is therefore a question that deserves additional research, as previously pointed out by Kamis et al. [17], Franke and Schreier [14] and Franke et al. [11]. 2.2. Consumer perceived benefits of a mass-customization experience Previous mass-customization research (e.g., [11,12,14,16]) has identified two benefits that a consumer can derive not from the possession of a mass-customized product, but from the experience of self-customizing such a product using a sales configurator. Based on that research stream, we respectively refer to these two potential benefits of a mass-customization experience as creativeachievement benefit and hedonic benefit. Creative-achievement benefit derives from the capacity of the mass-customization experience to arouse pride of authorship [16]. In general, pride is a positive emotion of self-reward that follows the assessment of one’s competences in a situation that is, in some measure, challenging [69–71], such as an exam or climbing a mountain. Pride of authorship, in particular, is the feeling of pride that an individual experiences whenever he/she creates, or at least has a sense of being the creator of an artifact that constitutes positive feedback on his/her own competences [16]. This definition implies that two conditions must be satisfied in order for an individual to feel pride of authorship. First, the individual must have perceived some degree of control over the characteristics of an artifact, thus experiencing the artifact as an extension of oneself. This condition clearly includes building something with one’s own hands, but may also mean selecting the features of a product or coming up with new product feature combinations using a sales configurator [11,16,21,65]. When self-customizing a product, the individual invests personal effort, time and attention in defining the characteristics of the product and, hence, psychic energy is transferred from the self to the product [16,72,73]. As a result, the

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product is regarded as part of oneself and is incorporated into the extended self [16,73,74]. Franke et al.’s [11] empirical study supports the idea that the experience of self-customizing a product with a sales configurator, despite the relatively limited investment involved, gives the configurator user a sense of being the creator of the configured product. This is insufficient, however, to arouse pride of authorship. The second condition for the existence of pride of authorship is that the artifact an individual has created in some measure, elicits positive feedback on his/her competences. Otherwise, the artifact could, rather, give a negative feeling of incompetence and the impression of having wasted time and effort [75,76]. This latter condition implies that, for a mass-customization experience to yield creative-achievement benefit, the sales configurator user must perceive the configured product as fitting, at least to some degree, his/her requirements [11]. To stress that the creative-achievement benefit derives not only from the ability of the mass-customization experience to give a potential customer a sense of being the creator of the configured product, but also from the perceived preference fit of the product, this experiential benefit is characterized as being ‘‘output-oriented’’ [16], where the term ‘‘output’’ refers to the configured product. Unlike creative-achievement benefit, hedonic benefit stems only from the characteristics of the mass-customization experience and, therefore, may be enjoyed even though a potential customer does not complete the configuration task. Hedonic benefit derives from the capacity of the mass-customization experience to be intrinsically rewarding [16]. There may be various reasons why a generic activity can be an end in itself, thus implying the actor’s positive affect (enjoyment, contentment, satisfaction, etc.) [77]. The activity of self-customizing a product with a sales configurator, in particular, may be perceived as intrinsically rewarding because it is entertaining like a game [12] or because it gives continuous visual feedback about the configuration choices made by a potential customer [17]. Unsurprisingly, the desire to have an exciting experience is found by Fiore et al. [78] as predicting customers’ willingness to engage in mass-customization experiences. To emphasize that hedonic benefit derives only from the characteristics of the mass-customization experience, and not also from those of the configured product, this experiential benefit is characterized as being ‘‘process-oriented’’ as opposed to ‘‘output-oriented’’ [16]. Be it gratifying per se or because, in combination with the configured product, it arouses pride of authorship, a rewarding mass-customization experience ‘‘creates a positive ‘mood’, which is carried over to the assessment of product value’’ ([14], p. 1029). As a result, willingness to pay for the mass-customized product rises [11,14]. This finding is consistent with consumer research results concerning shopping experiences in general, which do not necessarily involve mass-customized products. For example, Mochon et al. [76] find that feelings of pride associated with assembling a LEGO car elevate potential customers’ moods and positively impact on their willingness to pay for the car. Designing mass-customization experiences that trigger positive emotional responses among potential customers is therefore one way mass customizers can command a higher price premium for their products. Additionally, by designing gratifying mass-customization experiences, mass customizers may increase their sales volumes, as rewarding shopping experiences lead to unplanned shopping decisions [79], longer time spent while shopping [80] and higher repurchase intentions [17,81,82]. Larger sales volumes and consumers’ augmented willingness to pay translate into higher sales revenues and, all other things being equal, greater profitability of mass customizers. This means that increasing consumer-perceived hedonic and creative-achievement benefits is one key in augmenting the value of mass customization on the manufacturer’s side as well.

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3. Research hypotheses To improve the current understanding of what characteristics of a sales configurator increase the consumer-perceived benefits of a mass-customization experience, we draw upon the five sales configurator capabilities conceptualized by Trentin et al. [64] based on previous research on sales configurators. For each of these capabilities, hypotheses about their effects on both hedonic and creative-achievement benefits are developed in the following subsections. 3.1. Flexible navigation capability effects on hedonic and creativeachievement benefits Flexible navigation capability is the ability of a sales configurator to let its users easily and quickly modify a product configuration they have previously created or the one they are currently creating [64]. This capability implies allowing the user to change, at any stage of the configuration process, the choice he/she made at any previous stage without having to begin the process all over again [26,64]. This capability also implies enabling the user to bookmark his/her work and, therefore, to immediately recover a previous configuration in case he/she decides to reject the newly created one [26,64]. By allowing the user to make and undo changes to a current or previously created configuration more easily and more quickly, a sales configurator with a higher level of flexible navigation capability facilitates the exploration of a company’s product space [64]. By doing so, the sales configurator helps fulfill individuals’ intrinsic need for exploration. A desire for exploration, where exploration is seen as an end in itself because it provides individuals with a satisfactory level of stimulation from the environment [83–85], has been well documented in literature [83,86]. Individuals’ desire for exploration is evidenced by a variety of consumer behaviors, such as the early adoption of new products or the search for information about different product solutions out of curiosity. These behaviors are all, at least in part, intrinsically motivated by the desire to maintain stimulation at a satisfactory level [83,84]. By easing intrinsically driven exploration of a company’s product space, a sales configurator with a higher level of flexible navigation capability makes the user’s mass-customization experience more intrinsically rewarding. Based on the above argument and recalling that the capacity of a mass-customization experience to be gratifying per se leads to hedonic benefit, we posit that: H1. The higher the level of flexible navigation capability deployed by a sales configurator, the greater the hedonic benefit that a consumer derives from a mass-customization experience relying on that configurator. Intrinsically motivated exploration, which Raju and Venkatesan [87] call intrinsic exploration, is to be distinguished from extrinsic exploration, which serves as a means to some other goal [87]. The exploration of a company’s product space, for instance, may be intrinsically driven by curiosity, or may be extrinsically prompted by the desire to make better purchase decisions, or both. A sales configurator with a higher level of flexible navigation capability facilitates product space exploration in general [64], including extrinsic exploration. Making extrinsic exploration easier means allowing the sales configurator user to conduct more trial-anderror tests to evaluate the effects of his/her initial choices and to improve upon them. By doing so, the consumer learns about the available options and the value he/she would derive from them [21,60]. When finally opting for a certain configuration, the consumer is therefore more confident that the selected solution is

the one that best fits his/her needs within the company’s product space [64]. In other terms, by easing extrinsic exploration of the company’s product space, a higher level of flexible navigation capability leads to better perceived fit of the configured product with the consumer’s preferences. Besides perceived preference fit, this sales configurator capability also promotes the consumer’s feeling of being the creator of the configured product. A higher level of flexible navigation capability makes it easier for a consumer to move through the available options in a self-directed, non-sequential manner, which makes the mass-customization experience more interactive [61,88,89]. This nonlinear, trial-and-error process provides greater control for the consumer [88], meaning that the consumer perceives higher freedom of action [17]. A larger degree of control over the mass-customization experience makes the consumer attribute the outcome of that experience (i.e., the configured product) more to his/her own accomplishment [11]. Based on the above arguments and recalling that both the consumer’s perceived contribution to the configured product and its perceived fit with the consumer’s preferences drive creativeachievement benefit, we posit that: H2. The higher the level of flexible navigation capability deployed by a sales configurator, the greater the creative-achievement benefit that a consumer derives from a mass-customization experience relying on that configurator. 3.2. Focused navigation capability effects on hedonic and creativeachievement benefits Focused navigation capability is the ability of a sales configurator to quickly focus a potential customer’s search on those solutions of a company’s product space that are most relevant to the customer himself/herself, such as those that are most likely to satisfy his/her idiosyncratic needs [64]. This capability implies presenting the product space by product attributes and enabling the sales configurator user to freely prioritize his/her choices regarding the various attributes. A user looking for the solution that best fits his/her needs, for example, would be allowed to start from those attributes for which his/her preferences are most welldefined [61,64]. Instead, a user characterized by variety-seeking behavior [90], just to make another example, would be enabled to start from those attributes that offer more possibilities of choice. It is also noteworthy that, while requiring that the product space be presented by product attributes, this capability does not exclude the possibility that complete product alternatives are shown as well. This could be shown, for example at the beginning of the configuration process [26] to give the customer practice at evaluating alternatives and to provide anchors for the evaluative process [55]. A sales configurator with a higher level of focused navigation capability enables the consumer to more quickly eliminate options he/she regards as certainly inappropriate or uninteresting from further consideration. Consequently, the consumer can invest more time and effort in exploring that subset of a company’s product space that he/she perceives as most relevant to his/her interests or needs [64]. As perceived personal relevance based on one’s needs, values and interests is the essential characteristic of involvement [91,92], this means that focused navigation capability allows the consumer to focus his/her search on the part of a firm’s product space that he/she is most involved with. Involvement, in the context of an online experience, is an important precursor to attaining flow [93]. Flow, in that context, is defined as a seamless, deeply absorbing, self-reinforcing and intrinsically enjoyable interaction between the individual and the computer-mediated environment [88,93]. By increasing involvement and thus

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facilitating the experience of flow, a sales configurator with a higher level of focused navigation capability makes the masscustomization experience more intrinsically satisfying, as also suggested by research on entertaining shopping experiences [94]. Based on the above argument and recalling that the capacity of a mass-customization experience to be gratifying per se leads to hedonic benefit, we posit that: H3. The higher the level of focused navigation capability deployed by a sales configurator, the greater the hedonic benefit that a consumer derives from a mass-customization experience relying on that configurator. By facilitating the experience of flow, focused navigation capability also promotes the consumer’s feeling of being the originator of the configured product. This is because one of the key consequences of the flow experience for a consumer interacting with a computer-mediated environment is a perceived sense of control over his/her interaction [88,95]. Perceived control is meant here as the emotional response of dominance in environmental psychology [17] and, therefore, captures ‘‘the extent to which he [the individual] feels unrestricted or free to act in a variety of ways’’ ([96], p. 19). Therefore, a consumer using a sales configurator with a higher level of focused navigation capability perceives greater freedom of action during his/her mass-customization experience. In turn, the greater freedom perceived by the consumer makes him/her attribute the outcome of the mass-customization experience, that is the configured product, more to his/her own accomplishment [11]. In addition to greater subjective contribution, the user perceives better fit of the configured product with his/her preferences. This is because a sales configurator with a higher level of focused navigation capability enables the consumer to sequence his/her choices about the various attributes of the product by starting with those for which his/her preferences are most well-defined [64]. As lower preference uncertainty implies lower anticipated regret1 [98,99], and the anticipation of postdecisional regret promotes decision aversion [100], this means that focused navigation capability prevents the consumer from getting stuck with his/her early decisions. Conversely, the consumer can quickly reduce the size of his/her search problem [64]. Once the available solutions have been screened to a relevant set, called the consideration set [101], the consumer can analyze the remaining options in greater detail [101–103]. For example, the consumer may conduct more trial-and-error experimentation to learn about the remaining options, for which his/her preferences are less certain, and can rely on more time-consuming decision strategies that enable rational resolution of any trade-offs between attractive attributes. As a result, the consumer is more confident, at the end of the configuration process, that the chosen solution is the one that best fits his/her needs within the company’s product space [64]. In accord with this argument, Huffman and Kahn [55] find that presenting a company’s product space by product attributes, rather than by product alternatives, significantly increases the consumer’s feeling of being ready to make a choice at the end of the mass-customization experience. Based on the above arguments and recalling that both the consumer’s perceived contribution to the configured product and its perceived fit with the consumer’s preferences drive creativeachievement benefit, we posit that: H4. The higher the level of focused navigation capability deployed by a sales configurator, the greater the creative-achievement

1 Regret is a negative, cognitively determined emotion that individuals experience when realizing or imagining that their present situation would have been better, had they acted differently [97].

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benefit that a consumer derives from a mass-customization experience relying on that configurator. 3.3. Benefit-cost communication capability effects on hedonic and creative-achievement benefits Benefit-cost communication capability is the ability of a sales configurator to effectively communicate the consequences of the configuration choices made by a potential customer both in terms of what he/she would get and in terms of what he/she would give [64]. On the one hand, this capability implies effectively explaining the benefits the customer would derive from consumption of the configured product, including what the product can do, how well the product implements its functions, how well the product appeals to the five senses, etc., depending on the product category [12]. On the other hand, this capability implies clearly communicating the monetary and nonmonetary sacrifices that the customer would bear for obtaining the configured product, for example, by warning the customer that certain options entail longer delivery lead-times [61]. It is noteworthy that this capability implies communicating the benefits and costs associated with the entire set of configuration choices made by a potential customer, collectively considered,2 as well as the consequences of each of those choices [64]. This means, for example, explaining the way in which different options influence the functions and performance levels of the product and displaying the prices of the individual options [61]. A sales configurator with higher benefit-cost communication capability better supports potential customers in anticipating, during their mass-customization experiences, the value they will perceive from consumption of their configured products [64].3 In particular, higher benefit-cost communication capability leads to mass-customization experiences that more closely simulate consumers’ real-world interactions with their configured products, for example, through three-dimensional Web and virtual try-on technologies [106,107]. In other terms, a sales configurator with higher benefit-cost communication capability is more effective in transporting potential customers in a virtual environment where they can interact with their configured products as they do in the real world. This sensation of being present in a computer-mediated environment is known in literature as telepresence [89,108]. By giving potential customers a stronger sense of telepresence, a sales configurator with higher benefit-cost communication capability makes the mass-customization experience more intrinsically rewarding [89,106]. This is because ‘‘the experience of telepresence involves consumer fantasy, imagination and suspension of disbelief, suggesting elements of fun and playfulness (much akin to playing games)’’ ([89], p. 659). Accordingly, telepresence is acknowledged in literature as a contributor to the intrinsically enjoyable experience of flow [88,95]. Based on the above argument and recalling that the capacity of a mass-customization experience to be gratifying per se leads to hedonic benefit, we posit that: H5. The higher the level of benefit-cost communication capability deployed by a sales configurator, the greater the hedonic benefit that a consumer derives from a mass-customization experience relying on that configurator.

2 Product performance characteristics such as esthetics, power consumption or noise arise from the physical properties of most, if not all of the components of a product [104] and, therefore, are typically associated with the whole set of configuration choices made by a potential customer. 3 Perceived product value is defined as the customer’s ‘‘overall assessment of the utility of a product based on perceptions of what is received and what is given’’ ([105], p. 14).

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Since benefit-cost communication capability, like focused navigation, contributes to the experience of flow, it also promotes the consumer’s feeling of being the creator of the configured product, as previously explained in Section 3.2. Furthermore, benefit-cost communication capability increases perceived preference fit of the configured product. By delivering clearer prepurchase feedback on the effects of the configuration choices made by a potential customer, a sales configurator with higher benefitcost communication capability facilitates the user’s learning about the complex relationships linking the available options with the functions and performance levels of the product [61]. Better knowledge of such links gives the consumer a sounder basis upon which to make his/her purchase decision [61], thus increasing his/ her confidence that the product configuration eventually purchased is the one that best fits his/her needs within the company’s product space [64]. Based on the above arguments and recalling that both the consumer’s perceived contribution to the configured product and its perceived fit with the consumer’s preferences drive creative-achievement benefit, we posit that: H6. The higher the level of benefit-cost communication capability deployed by a sales configurator, the greater the creative-achievement benefit that a consumer derives from a mass-customization experience relying on that configurator. 3.4. User-friendly product space description capability effects on hedonic and creative-achievement benefits User-friendly product space description capability is the ability of a sales configurator to adapt the description of a company’s product space to the individual characteristics of a potential customer as well as to the situational characteristics of his/her using of the sales configurator [64]. This capability implies adapting the information content presented to the potential customer, for example, by offering different types of choices according to his/her prior knowledge about the product. Expert customers should be presented choices involving alternative product components, while inexpert customers, who are unable to relate product components specifications to satisfaction of their needs, should be offered choices involving functions and performance levels of the product [26,61,64]. Furthermore, this capability ensures that the provision of information about an option that matters only to a few potential customers does not impose research costs on the majority of them [102]. Besides information type and quantity, this capability implies adapting information format as well, for example, by presenting the same content through different media (texts, images, animation, etc.) in order to satisfy sales configurator users varying in skill level, cognitive style, age, etc. [64,109]. By tailoring both information content and information format to the characteristics of different potential customers as well as to different usage contexts, a sales configurator with user-friendly product space description capability reduces the risk of information overload [110–112]. On the one hand, the user is not forced to process information content he/she does not value [113]. On the other end, the modality of presentation of the same information content is switched, or augmented, in such a way that the user’s information processing is enhanced [114]. As a result of these two combined mechanisms, the user perceives his/her skills as equal to the challenges of the configuration task. Perceived congruence between the challenges of a task and an individual’s ability to perform it is an important antecedent of the flow experience, provided the challenges exceed the level that is typical for the dayto-day experiences of the individual [88]. As the challenges of the configuration task tend to exceed such a critical threshold, unless the set of available choice options is very small [17], this means that user-friendly product space description capability facilitates

the experience of flow, thus making the mass-customization experience more intrinsically satisfying [88]. Based on the above argument and recalling that the capacity of a mass-customization experience to be gratifying per se leads to hedonic benefit, we posit that: H7. The higher the level of user-friendly product-space description capability deployed by a sales configurator, the greater the hedonic benefit that a consumer derives from a mass-customization experience relying on that configurator. Since user-friendly product space description capability, like the ones of benefit-cost communication and focused navigation, facilitates the experience of flow, it also promotes the consumer’s feeling of being the creator of the configured product, as previously explained in Section 3.2. Furthermore, user-friendly product space description capability increases perceived preference fit of the configured product. This is because the product space is presented to the consumer exactly in the way he/she is able or willing to express his/her needs [64]. This makes it easier for the consumer to assess the fit of the configured product with his/her needs [56]. Consequently, at the end of the configuration process, the consumer is more confident that the chosen solution is the one that best fits his/her needs within the company’s product space [64]. Based on the above arguments and recalling that both the consumer’s perceived contribution to the configured product and its perceived fit with the consumer’s preferences drive creative-achievement benefit, we posit that: H8. The higher the level of user-friendly product-space description capability deployed by a sales configurator, the greater the creative-achievement benefit that a consumer derives from a mass-customization experience relying on that configurator. 3.5. Easy comparison capability effects on hedonic and creativeachievement benefits Easy comparison capability is the ability of a sales configurator to support its users in comparing product configurations they have previously created [64]. This capability implies allowing the user to save a product solution he/she has just configured and then compare previously saved configurations on the same screen [26,64]. This capability also implies highlighting commonalities and differences among previously saved configurations as well as rank-ordering them based on some criterion that is meaningful to the user [64]. A sales configurator with a higher level of easy comparison capability unburdens the user from the weight of mentally or manually recording information about the product solution he/she is creating, in order to subsequently compare it with other configurations. It also compensates for the user’s limited computational abilities whenever the number of customizable product attributes is high and the user needs to delineate previously created configurations into their attributes to find out similarities and differences among them [64]. Unless a company’s product space is very simple, therefore, higher levels of this capability are important to help the user grasp the differences between the product solutions he/she is comparing. By making such differences more salient, a sales configurator with a higher level of easy comparison capability supports intrinsically motivated exploration of a company’s product space, that is exploration primarily for the pleasure inherent in changing the stimulus field [83,87]. By helping the user perceive the amount of change and novelty he/she has effected in the stimulus field, such a sales configurator makes the user’s mass-customization experience more intrinsically rewarding. Based on the above argument and recalling that the capacity of a mass-customization

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experience to be gratifying per se leads to hedonic benefit, we posit that: H9. The higher the level of easy comparison capability deployed by a sales configurator, the greater the hedonic benefit that a consumer derives from a mass-customization experience relying on that configurator. A sales configurator with a higher level of easy comparison capability also promotes the user’s feeling of dominance in his/her mass-customization experience. This feeling is enhanced by settings that facilitate a greater variety of behaviors [96]. When using a sales configurator with higher levels of this capability, consumers are not restricted by their limited working memory, or by their limited time availability for manually recording information, to compare only two solutions at a time. Furthermore, consumers are free to control the basis for comparison, an opportunity that is typical of in-store shopping but must not be taken for granted when on-line shopping [102]. As a consumer is offered a larger degree of control over his/her mass-customization experience, he/she attributes the outcome of such an experience, that is the configured product, more to his/her own accomplishment [11]. In addition to greater subjective contribution, the consumer perceives better fit of the configured product with his/her preferences. This is because comparisons of complete product solutions play an important role in the consumer’s assessment of the value of a particular product solution [115,116]. By supporting such evaluations, a higher level of easy comparison capability fosters the consumer’s learning about the value he/she would derive from consumption of the product being configured [64]. In turn, this learning process makes the consumer more confident that the configuration for which he/she finally opts is the one that best fits his/her needs within the company’s product space [64]. Based on the above arguments and recalling that both the consumer’s perceived contribution to the configured product and its perceived fit with the consumer’s preferences drive creativeachievement benefit, we posit that: H10. The higher the level of easy comparison capability deployed by a sales configurator, the greater the creative-achievement benefit that a consumer derives from a mass-customization experience relying on that configurator. An overview of the hypothesized relationships between the five sales configurator capabilities of interest and the hedonic and creative-achievement benefits of a mass-customization experience is provided by Fig. 1.

Flexible navigaon

Focused navigaon

Hedonic benefit

Benefit-cost communicaon Creaveachievement benefit

User-friendly product space descripon Easy comparison

Fig. 1. Hypothesized relationships.

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4. Method To test the hypothesized links, we designed an empirical study replicating the data collection procedure adopted by Trentin et al. [64] for large-scale validation of their measures of the focal salesconfigurator capabilities. The participants in the study were 75 engineering students (30% females) with ages ranging from 24 to 27 years. As a consequence, our data are biased in favor of young males. Each participant was asked to make one mass-customization experience on each of nine pre-assigned Web-based sales configurators, for a total of 675 mass-customization experiences. Each experience involved browsing the sales configuration website and configuring one product from start to finish, on that website, according to one’s own preferences. For each experience, participants filled out a questionnaire covering the constructs of interest. The five sales-configurator capabilities were measured using the multi-item scales proposed and validated by Trentin et al. [64], while the measures of hedonic and creativeachievement benefits were adapted from Merle et al.’s [12] scales (see Appendix A). Adaptation was motivated by an acknowledged limitation of Merle et al.’s [12] instrument: namely, the fact that discriminant validity between the measures of hedonic benefit and creative-achievement benefit was supported by the chi-square difference test proposed by Bagozzi and Philipps [117] but not by Fornell and Larcker’s [118] procedure, which Hatcher [119] considers quite conservative [12]. The nine sales configurators assigned to each participant were chosen from a set of 30 real Webbased configurators of consumer goods for which the participants, on average, had sufficient preference insight and ability to express their preferences, as defined by Franke et al. [120]. The set included ten configurators of notebooks/laptops, nine configurators of sports shoes/sneakers and eleven configurators of economy cars. Preference insight and ability to express preferences were measured on a seven-point Likert scale (7 = completely agree, 1 = completely disagree) using the items proposed by Franke et al. [120]. The average scores of the two constructs across participants were, respectively: 4.24 (standard deviation: 1.64) and 4.16 (standard deviation: 1.56) for notebooks/laptops, 5.36 (standard deviation: 1.34) and 4.69 (standard deviation: 1.52) for sports shoes/sneakers, and 4.53 (standard deviation: 1.28) and 4.77 (standard deviation: 1.13) for economy cars.4 The inclusion of multiple product categories, ranging from relatively simple products with relatively few configuration steps to more complex products with more configuration steps, was motivated by the aim of increasing the variation ranges of the independent variables within our sample.5 To further increase the differences among the mass-customization experiences comprising our sample, we assigned sales configurators to participants according to the following rules: (i) no pairs of participants were assigned the same combination of configurators, (ii) each participant was assigned three configurators for each product category, and (iii) each of the triples assigned to each participant included at least one configurator with a high mean score of the five capabilities within 4 For both constructs, only one factor with eigenvalue greater than one was extracted using principal component analysis (variance explained: 86% and 85%, respectively). Cronbach’s alfas were 0.91 and 0.94, respectively. 5 Based on our previous studies on sales configurators, we were concerned about the risk of having insufficient variation in one or more of the five capabilities of interest in case of selection of real configurators for only one product category. The data collected in the present study indicate that our concern for that risk was not unwarranted. Within the subsample of mass-customization experiences made on the sports shoes/sneakers configurators, for instance, the standard deviation of benefit-cost communication capability – measured on a seven-point Likert scale – is as low as 0.35, while it reaches 1.01 within the entire sample. Likewise, within the subsample of mass-customization experiences made on the economy car configurators, flexible navigation capability – measured on the same seven-point Likert scale – is as low as 0.37, while it reaches 0.97 within the entire sample.

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700 Table 1 Discriminant validity. Square root of AVE

BCC EC FlexN FocN UFD HE CA

0.835 0.892 0.784 0.851 0.854 0.936 0.853

Correlationsa BCC

EC

FlexN

FocN

UFD

HE

CA

– 0.312 0.369 0.734 0.705 0.588 0.512

– 0.437 0.408 0.327 0.402 0.458

– 0.455 0.415 0.483 0.485

– 0.719 0.673 0.571

– 0.586 0.520

– 0.847

–

Note: AVE, average variance extracted; BCC, benefit-cost communication capability; EC, easy comparison capability; FlexN, flexible navigation capability; FocN, focused navigation capability; UFD, user-friendly product space description capability; HE, hedonic benefit; CA, creative-achivement benefit. a All correlations are significant at p < 0.001.

the corresponding product category and at least one configurator with a low mean score of the five capabilities within the same product category.6 Following data collection, we used structural equation modeling to test the hypotheses and LISREL 9.1 to conduct the analyses. Based on Anderson and Gerbing’s [121] two-step approach, we first assessed the psychometric properties of the measures of the focal constructs and subsequently estimated the full model, which also includes the hypothesized relationships. Since our variables did not meet the assumption of multivariate normal distribution (Mardia’s test significant at p < 0.001), in both phases we applied the Satorra-Bentler correction to produce robust maximum likelihood estimates of standard errors and chi-square (x2). Prior to conducting the analyses, we also controlled for possible effects of participants’ characteristics by regressing the items used as observed indicators of the focal constructs on 75 dummies representing the participants in our study. The standardized residuals from this linear, ordinary least square regression model were subsequently used as our data in both steps of the analysis (cf. [6,64,122]). In the first phase, we employed confirmatory factor analysis to assess measurement scale unidimensionality, convergent validity, discriminant validity and reliability for the seven constructs of interest. Unidimensionality and convergent validity were evaluated by estimating an a priori measurement model in which each of our items was restricted to load on the construct it was intended to measure and the seven latent constructs were free to correlate. This model well reproduced our sample data, as indicated by the values of the typical fit indices (RMSEA = 0.0528, x2/df (df) = 2.49 (209), CFI = 0.991, GFI = 0.928). Furthermore, all standardized factor loadings were positive and greater than 0.50 (see Appendix A). Altogether, these results suggested that, for each scale, its items measured a single construct (unidimensionality) and the various items, seen as different methods of measuring the same construct, provided the same results (convergent validity) [121,123,124]. Reliability, which indicates the degree to which a measure is free from random error, was assessed using both the average variance extracted (AVE) and the Werts, Linn, and Joreskog (WLJ) composite reliability (CR) method [125]. All AVE scores largely exceeded 0.50 and all WLJ CR values were greater than 0.70 (see Appendix A), indicating good reliability of our measurement scales [118,126]. Finally, discriminant validity, which refers to the extent to which measures intended to capture different constructs actually reflect separate

6 To apply this rule, one of the authors assessed the 30 sales configurators with respect to the five capabilities of interest, using the same measures included in the questionnaire. Subsequently, for each product category, the corresponding configurators were ranked by the average score of the five capabilities and, finally, were divided into three equal-size (or approximately equal-size) groups by rank (high, medium and low).

constructs, was assessed using Fornell and Larcker’s [118] procedure. For each of our seven constructs, the square root of the AVE exceeded the correlations with the other constructs in the model (see Table 1), thus indicating good discriminant validity of our measurement scales [118]. 5. Results After establishing measurement scale reliability and validity for the focal constructs, we estimated the full model including also the hypothesized relationships among those constructs. The model demonstrated acceptable fit across the typical fit indices (see Table 2). The normalized x2 (i.e., the x2 divided by the degrees of freedom) was within the suggested 1–3 range for acceptability [127]. The Root Mean Square Error of Approximation (RMSEA) was very close to 0.05 and lower than 0.08, thus suggesting good fit [128]. Finally, Goodness-of-Fit Index (GFI) and Comparative Fit Index (CFI) were both greater than the recommended level of 0.90 [129,130]. Furthermore, all the estimated path coefficients were positive, as hypothesized, and statistically significant at conventional levels (p < 0.05). Overall, these results indicated that the structural model reproduced the data well and that our hypotheses were all supported.

Table 2 Results of hypotheses tests. Hypothesized path

Hypothesis

Std. path coefficient

t-Value

FlexN ! HE FlexN ! CA FocN ! HE FocN ! CA BCC ! HE BCC ! CA UFD ! HE UFD ! CA EC ! HE EC ! CA

H1 H2 H3 H4 H5 H6 H7 H8 H9 H10

0.174 0.199 0.364 0.209 0.140 0.132 0.122 0.128 0.094 0.203

4.217*** 4.851*** 5.462*** 3.002*** 2.431* 2.041* 2.199* 2.056* 2.600** 4.913***

Fit statistics Normalized x2 = 2.49 (df = 209) RMSEA = 0.0528 GFI = 0.928 CFI = 0.991 Note: BCC, benefit-cost communication capability; EC, easy comparison capability; FlexN, flexible navigation capability; FocN, focused navigation capability; UFD, user-friendly product space description capability; HE, hedonic benefit; CA, creative-achivement benefit; RMSEA, Root Mean Square Error of Approximation; GFI, Goodness-of-Fit Index; CFI, Comparative Fit Index. Significant at: * p < 0.05. ** p < 0.01. *** p < 0.001.

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6. Discussion and conclusion The present paper contributes to the debate as to the role sales configurators can play in business-to-consumer mass-customization strategies. This debate has typically viewed the consumer’s experience of self-customizing a product with a sales configurator as a cost for the consumer himself/herself in terms of time spent, cognitive effort required and possible unpleasant emotional outcomes. Accordingly, this debate has typically focused on what characteristics a sales configurator should have to reduce both these costs on the consumer’s side and their negative repercussions on the company’s revenues due to lost sales and consumers’ lower willingness to pay [11,64]. The present paper complements this important perspective by considering the consumer’s masscustomization experience as a potential source of positive emotional responses that a sales configurator should promote to increase sales volumes and consumers’ willingness to pay, thus ultimately boosting the company’s revenues.7 Consistent with recent studies [12,16], our paper focuses on two potential benefits of a mass-customization experience: hedonic benefit, which derives from the capacity of the experience to be gratifying per se, regardless of the completion of the configuration task, and creative-achievement benefit, which stems from the capacity of the experience to arouse, in combination with the configured product, the positive emotion of pride of authorship. For each of these two potential benefits, we conceptually and empirically examine how it is influenced by the five sales configurator capabilities recently defined by Trentin et al. [64]: the ability to quickly focus customer research on those solutions of a company’s product offer that are most relevant to the customer himself/herself (focused navigation capability); the ability to adapt the description of the product offer to the individual characteristics of the potential customer as well as to the situational characteristics of his/her using of the sales configurator (user-friendly product space description capability); the ability to effectively communicate what the potential customer would get and what he/ she would give as a consequence of his/her configuration choices (benefit-cost communication capability); the ability to support the potential customer in comparing product configurations he/she has previously created (easy comparison capability); finally, the ability to let the potential customer easily and quickly modify a product solution he/she has previously configured or the one he/ she is currently configuring (flexible navigation capability). These five sales-configurator capabilities have been proposed by Trentin et al. [64] as one key in preventing product customization from backfiring, as they alleviate the cognitive and emotive difficulty experienced by a potential customer in configuring a product and making a purchase decision. In this paper, we hypothesize that the same sales configurator capabilities mentioned above increase consumer-perceived hedonic benefit because they help fulfill the individual’s intrinsic need for exploration and facilitate the intrinsically enjoyable online flow experience. In particular, we argue that they promote flow by matching the challenges of the configuration task with the individual’s ability to perform it, by giving the individual a stronger sense of presence in the computer-mediated environment and by increasing his/her perceived involvement with the explored product solutions. Furthermore, we hypothesize that the same five capabilities increase creative-achievement benefit for two reasons. First, they enhance the individual’s feeling of dominance in the mass-customization experience, thus promoting his/her sense of being the creator of the configured product. Second, they increase 7 Positive affect and lack of negative affect are considered as separate contributors to subjective well-being in general and consumer happiness in particular [131–134].

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perceived preference fit of the configured product and, therefore, the individual attributes a more favorable outcome to oneself. In addition to the development of the theoretical arguments for the abovementioned hypotheses, another contribution of the present paper lies in the empirical test of such hypotheses, which provides empirical support for all of them. This is among the first studies that empirically investigate the question of how sales configurators should be designed to trigger positive affective reactions on their users. It is noteworthy that the few findings available in literature on this issue are echoed by our results. Specifically, Kamis et al. [17] find empirical support for the hypothesis that a mass-customization experience is more intrinsically enjoyable as a sales configurator presents a company’s offer by product attributes and gives continuous interactive feedback through a visual representation of the chosen attribute levels. This finding is echoed by our result that hedonic benefit increases both with focused navigation capability, which implies presenting the product space by product attributes, and with benefit-cost communication capability, which implies delivering clear prepurchase feedback on the effects of the configuration choices made. Our paper adds to Kamis et al.’s [17] finding by considering the creative-achievement benefit, besides the hedonic one, and by indicating a broader set of sales configurator characteristics that predict each of these two benefits. While focusing on sales configurators, the present paper also contributes to the wider debate on the role that product configurators, which include sales configurator functionalities, can play in business-to-consumer mass-customization strategies. Several prior studies have shown that product configurators can help manufacturers mitigate the negative effects of product customization on cost, time and quality performance (e.g., [10,47,49]). Likewise, it is acknowledged in literature that product configurators can support consumers in identifying their own solutions while reducing computational and non-computational sources of decision difficulty (e.g., [25,26,64]). The present paper is among the few studies to show that product configurators can deliver additional benefits to consumers, by triggering positive emotional responses to their mass-customization experiences. Since these benefits lead to higher consumer willingness to pay [11,14] as well as to unplanned shopping decisions and higher repurchase intentions [79,82], this means that product configurators have a broader potential for augmenting mass customizers’ profitability than often recognized in literature. On the one hand, this conclusion reinforces the importance of information technology as an enabler of successful mass-customization strategies (e.g., [3,9,10,135–137]). On the other hand, this conclusion calls for future studies on technological solutions that reduce the costs of implementing the five capabilities in a product configurator. This is because, for the profitability improvement potential to materialize, any incremental revenues due to the five capabilities must not be negatively offset by the incremental costs of their implementation. While contributing to the academic debate as to the role of sales/product configurators in mass-customization strategies, this study is not without its limitations, which might be addressed in future research. First, we have developed our hypotheses with reference to mass-customization experiences involving consumer goods and, accordingly, have focused the hypothesis-testing portion of the study on sales configurators of consumer goods. Even though prior research has suggested that hedonic and creative-achievement benefits are more relevant in a business-toconsumer context [12,17], their definitions do not rule out the possibility of buyers of mass-customized industrial goods experiencing such benefits. Likewise, the definitions of the five focal capabilities do not rule out the possibility of sales/product configurators of industrial goods deploying them. Consequently, future research should examine to what extent our findings can be

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extended to mass-customization experiences involving buyers of industrial goods. A second limitation of our study lies in its using of engineering students as subjects for the research, which makes our data biased in favor of young males. Though most of the users of business-toconsumer sales configurators are young people adept at using the Internet [14,138], undeniably the participants in our study do not constitute a representative sample of the potential customers of the considered products. Consequently, future research should seek to replicate our findings in truly representative samples of potential customers. A third limitation of the present study is its focus on the main effects [139] of the five capabilities on the two benefits of interest. In line with this focus, we neglect possible interaction effects between the five capabilities as well as possible contingency effects of variables such as product complexity, the number of configuration steps, an individual’s optimum stimulation level [84] or his/her perceived involvement with the product category [92]. While our focus is consistent with the fact that the research on this topic is in its infancy, future studies should be designed to overcome this limitation. Another limitation of the present study lies in the lack of explanation for the differences we find in the individual impacts of the five capabilities on the two considered benefits. The differences we find in the magnitude of the estimated path coefficients indicate that some capabilities contribute more than others to the two benefits. Such differences are wider with respect to hedonic benefit, with focused navigation capability contributing the most and easy comparison capability contributing the least. On the other hand, the differences are smaller regarding creative-achievement benefit, with benefit-cost communication and user-friendly product space description capabilities contributing relatively less than the others. We did not develop hypotheses about the relative contributions of the five capabilities, however. Furthermore, because of the limitations mentioned above, we hesitate to generalize these findings. Additional conceptual and empirical research is needed, in our view, before conclusions about the relative contributions of the five capabilities to hedonic and creative-achievement benefits can be drawn.

A final limitation of our research is its lack of analysis of the costs for implementing the five capabilities. Further research should address this limitation, focusing on the enablers of the five capabilities. It is noteworthy that studies are multiplying on technological solutions, such as advances in body modeling [140], virtual reality [141], mixed-reality [142] and augmented reality [143], which promise to considerably enhance capabilities of prospective sales/product configurators such as benefit-cost communication or easy comparison. Our paper further reinforces the importance of such research endeavors and calls for additional studies in this direction. While relying on only three categories of consumer goods and on a non-representative sample of their potential customers, the present paper has a number of managerial implications, at least for those companies that offer those types of products. First, our paper increases practitioners’ awareness that sales/product configurators can be an effective tool to augment the consumer-perceived benefits of mass-customization experiences. Nowadays, mass-customization strategies are more and more widespread and, therefore, mass customizers may need to identify unexploited sources of differentiation advantage [144]. In such a context, increasing the hedonic and creative-achievement benefits of consumers’ mass-customization experiences can be one key in delivering benefits that exceed those of competing mass customizers’ offerings. This may sound particularly attractive to mass customizers producing in higher-labor-cost countries. These companies may have a difficult time competing only on efficient customization as mass-customization strategies are increasingly adopted in lower labor-cost countries as well [145]. Secondly, the present paper indicates specific sales/product configurator capabilities that augment the hedonic and creative-achievement benefits of consumers’ mass-customization experiences. These capabilities represent clear objectives that companies should pursue in selecting or building their sales/product configurators if they decide to deliver such benefits. However, before such managerial indications can be generalized to industrial goods and professional users of sales/product configurators such as buyers, further research is needed.

Appendix A. Measures of the constructs of interest For each item, respondents indicated the extent to which they agreed or disagreed with the statement on a seven-point Likert scale (7 = completely agree,. . ., 1 = completely disagree). Standardized factor loadinga Benefit-cost communication capability (BCC) b (AVE: 0.697; CR: 0.873) BCC1 Thanks to this system, I understood how the various choice options influence the value that this product has for me BCC2 Thanks to this system, I realized the advantages and drawbacks of each of the options I had to choose from BCC3 This system made me exactly understand what value the product I was configuring had for me Easy comparison capability (EC) b (AVE: 0.796; CR: 0.939) EC1 The system enables easy comparison of product configurations previously created by the user EC2 The system lets you easily understand what previously created configurations have in common EC3 The system enables side-by-side comparison of the details of previously saved configurations EC4 The systems lets you easily understand the differences between previously created configurations Flexible navigation capability (FlexN) b (AVE: 0.614; CR: 0.826) FlexN1 The system enables you to change some of the choices you have previously made during the configuration process without having to start it over again With this system, it takes very little effort to modify the choices you have previously made during the configuration process FlexN2 FlexN3 Once you have completed the configuration process, this system enables you to quickly change any choice made during that process Focused navigation capability (FocN) b (AVE: 0.724; CR: 0.913) FocN1 The system made me immediately understand which way to go to find what I needed FocN2 The system enabled me to quickly eliminate from further consideration everything that was not interesting to me at all FocN3 The system immediately led me to what was more interesting to me FocN4 This system quickly leads the user to those solutions that best meet his/her requirements

0.858 0.792 0.853 0.894 0.948 0.807 0.913 0.738 0.789 0.822

0.857 0.791 0.893 0.860

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Appendix A (Continued ) Standardized factor loadinga User-friendly product space description capability (UFD) b (AVE: 0.729; CR: 0.890) UFD1 The system gives an adequate presentation of the choice options for when you are in a hurry, as well as when you have enough time to go into the details The product features are adequately presented for the user who just wants to find out about them, as well as for the user who UFD2 wants to go into specific details The choice options are adequately presented for both the expert and inexpert user of the product UFD3 Hedonic benefit (HE) c (AVE: 0.876; CR: 0.955) I found it fun to customize this product HE1 HE2 Customizing this product was a real pleasure HE3 Customizing this product was like a game Creative-achievement benefit (CA) c (AVE: 0.727; CR: 0.900) CA1 I felt really creative while configuring this product CA2 The company gave me a lot of freedom while creating this product CA3 By personalizing this product, I had the impression of creating something a b c

0.883 0.907 0.766 0.961 0.956 0.888 0.923 0.762 0.865

All factor loadings are significant at p < 0.001. Trentin et al. [64]. Adapted from Merle et al. [12].

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Cipriano Forza is a full professor of operations management at the Universita` di Padova (Italy). He is also on the faculty at the European Institute of Advanced Studies in Management, where he teaches Research Methods in Operations Management. He has been a visiting scholar at Minnesota University (USA), London Business School (UK) and Arizona State University (USA). Currently he serves as an associate editor for the Journal of Operations Management and the Decision Sciences Journal. His research focuses on product variety management, including such topics as mass customization, concurrent product-processsupply chain design and product configuration. He has been successfully assisting numerous companies in these areas. His work has been published in the Journal of Operations Management, the International Journal of Operations & Production Management, the International Journal of Production Research, Computers in Industry, the International Journal of Production Economics, Industrial Management & Data Systems and other journals. In 2003 and 2007 he published two books with McGraw-Hill and Palgrave Macmillan, respectively, on product information management for mass customization.