Optimal Consumer Electronics Product Take-Back Time with Consideration of Consumer Value

sustainability

Article Optimal Consumer Electronics Product Take-Back Time with Consideration of Consumer Value

Yi-Tse Fang and Hsin Rau * Department of Industrial and Systems Engineering, Chung Yuan Christian University, Taoyuan City 32023, Taiwan; [email protected] * Correspondence: [email protected]; Tel.: +886-3-265-4417

Academic Editor: Bhavik Bakshi Received: 21 September 2016; Accepted: 2 March 2017; Published: 7 March 2017

Abstract: Rapid economic growth in recent years has transformed our lifestyle to massively produce, consume, and dispose of products, especially for consumer electronics. This change has put great threat to our environment and caused natural resource depletion. Moreover, short product life cycles and quick replacements of consumer electronics create enormous electronic wastes (e-wastes). Without proper waste management, immense environmental damage is expected. In this empirical study, we notice that lots of valuable materials that can still be recycled from these used consumer electronics are left unused at home instead of being recycled at the appropriate time, which causes a low collection rate and a decrease in residual value for the used products. Therefore, it is important for the government and the recyclers to handle them efficiently by increasing the used product take-back rate. Our study develops an assessment model for customer value based on the idea of value engineering and the perspective of product life cycle. We also explore the relationship between product value and the total cost of ownership with an evaluation of their time variation, considering different usage modes for various consumer groups and different recycling award schemes (fixed and variable recycling awards). Proper take-back management is likely to create a win-win situation both for consumers and environmental protection. This study regards the notebook computer as an example to determine the optimal time for recycling laptops based on usage patterns and provides consumers a reference for when to replace their used product. The results from our modeling firstly clearly indicate that consumers with higher frequency of usage have shorter take back times and higher maximum consumer value. Secondly, a variable recycling award scheme with higher maximum consumer value is more practical than a fixed recycling award scheme.

Keywords: product take-back time; consumer value; total cost of ownership; recycling award

1. Introduction The rapid development of technology has brought consumer electronics into our daily life in the past decades. This has changed the way we communicate, entertain, and obtain information. Innovative technology continuously pushes out the old model and brings in the new one to meet consumer’s demands. This has shortened the life cycle of consumer electronics and resulted in greater replacement and disposal compared to other products. Without proper recycling processes, these accumulated electronic wastes (e-waste) will not only pose threats to the ecological environment but also cause valuable resources to be destroyed or unused. According to the research of Balde et al. [1], the estimated amount of e-waste generated in 2014 was 41.8 million metric tonnes (Mt), and this was forecasted to increase to 50 Mt of e-waste in 2018. In Europe [2], e-waste is increasing at an annual rate of 3% to 5%, which is almost three times faster than the total waste stream. Developed countries are not the only ones that generate e-waste; developing countries are also expected to triple their e-waste production. United Nations Environment Program (UNEP) [3] estimated that 50 million tons of

Sustainability 2017, 9, 385; doi:10.3390/su9030385 www.mdpi.com/journal/sustainability Sustainability 2017, 9, 385 2 of 17 e-wastes are produced each year globally, but only 15%–30% of e-waste is recycled; the rest go directly to landfills and incinerators. In addition, US government researchers [4] investigated the quantity of electronic products ready for end-of-life between 1990 and 2010; the result implies that 5 million short tons of electronic products are in storage, remain stockpiled, and are waiting for disposal. Today’s computer industry innovates at a rapid pace and brings new technologies with upgrades to market on average of every 18 months. According to data provided by the Statist a website [5], the average life of PCs and tablets is expected to drop in the next four years. While the average life for these devices was almost 3.1 years in 2013, that number is expected to drop to a little over 2.8 years by 2017. It shows that computer replacement has increased and caused a huge disposal problem. Kwak et al. [6] presented the results of an analysis of data collected from an e-waste collection center in Chicago, showing that the mean age of collected laptop computers is 11 years old, which is very different from its typical wear-out lifespan. United States Environmental Protection Agency (U.S. EPA) [7] discovered that many consumers did not recycle their consumer electronic products when they first became defunct or obsolete and more than 70% of retired products were kept in storage, typically for as many as 3–5 years. In order to resolve these serious waste problems caused by consumer electronics, the European Union proposed an Integrated Product Policy (IPP) [8] that aims to take a life cycle perspective instead of the end-of-pipe treatment. Integrated environmental awareness is blended into the processes from design, extraction of natural resources, manufacturing, assembly, distribution, and use to the eventual disposal as waste to reduce damage and pressure on the environment. It also needs to include all relevant stakeholder viewpoints for the whole product development process from idea generation to product management and reverse logistics. End-of-life management (EOLM) has become an important global issue in electronic consumer products, home appliances, and industrial equipment products recently. Many enterprises have successfully applied this management method as a feasible solution to solve the E-waste problem. Ramani et al. [9] define EOLM as the process of converting end-of-life products into remarkable products, components, or materials. It enables manufacturers to comply with environmental legislation while gaining economic advantages. EOLM can be divided into two parts: (1) product take-back, which is the process of acquainting the end of life products from the consumer; and (2) EOL recovery options, which take the products after the acquisition to elect product reuse, component reuse, and material recovery options [10–12]. Guide et al. [13] considered the uncertainty of quality and quantity, as well as the timing of end-of-life products that made EOLM difficult. In line with that dilemma, Rayet al. [14] proposed the concept of an active product recovery system. They believe that, through economic incentives, there is an opportunity to enhance consumer product recycling to achieve an economy of scale. While others addressed the issue as a problem of scheduling take-back, a problem in the demand for parts or recovered products with the objective to fulfill the demand at a minimum cost. White et al. [15] presented an overview of the EOLM problems existing in each stage of the product recovery process and showed that better information about product design, product quality, and timing can improve the product EOL opportunities. Zhao et al. [16] developed a model to help the manufacturers determine optimal take-back time and the number of lifecycles for warranty purposes. In addition, some literature explored recycling facility locations and the number of resource allocations for the optimal recycling solutions [17–19]. As summarized above, most of the product manufacturers (recyclers) explore an end of life product recycling strategy, with the goal either to identify product recovery process to obtain maximum profits at minimum cost or to reduce the impact on the environment. Conversely, only a few papers considered the value of the consumer, but none uses consumer value to study take-back time for consumer electronics, based on our best knowledge. This motivates our study. However, if we want to reduce the environmental impacts throughout the life cycle of a product, all the different actors and stakeholders, such as designers, manufacturers, consumers, and recyclers, should participate. In this study, in order to help consumers understand the perfect timing for the take-back of a laptop computer, Sustainability 2017 9 Sustainability 2017,, 9,, 385385 3 of 17 of a laptop computer, we have developed an assessment model from the consumer’s position and we have developed an assessment model from the consumer’s position and taken the point of view taken the point of view of a product life cycle to construct the consumer value over time. We have of a product life cycle to construct the consumer value over time. We have also considered the usage also considered the usage patterns of various consumer groups to obtain their different optimal take- patterns of various consumer groups to obtain their different optimal take-back times and to provide back times and to provide different consumers with a reference for their product replacement. different consumers with a reference for their product replacement. This paper is organized as follows. In addition to this introduction, Section 2 develops a This paper is organized as follows. In addition to this introduction, Section2 develops a proposed proposed assessment model. Section 3 illustrates the proposed assessment model using real data on assessment model. Section3 illustrates the proposed assessment model using real data on laptop laptop computers. Finally, Section 4 gives a conclusion with suggestions for future research. computers. Finally, Section4 gives a conclusion with suggestions for future research.

2. Model Development Value engineeringengineering (VE) is a powerful technique to determine the best relationshiprelationship between cost and value by analyzing product and process performance. It could be introduced at any point in the life-cycle ofof products,products, systems,systems, or or procedures procedures [ 20[20].]. This This study study proposes proposes a a consumer consumer value value model model that that is basedis based on on the the idea idea of of VE VE and and the the perspective perspective of of product product life life cycle. cycle. The The consumer consumer value value is ais function a function of time,of time, and and this this study study uses uses it to it determine to determine the optimal the optimal take-back take-back time from time the from consumer the consumer aspect duringaspect during the product life cycle. The consumer value (VC(t)) can be defined as the ratio of product value the product life cycle. The consumer value (VC(t)) can be deﬁned as the ratio of product value (VP(t)) and(VP(t total)) and cost total of cost ownership of ownership (TCO( t()).TCO The(t)). product The product value isvalue the valueis the thatvalue the that consumer the consumer obtains obtains in his orin his her or holding her holding time, andtime, the and total the costtotalof cost ownership of ownership is the is cost the thatcost thethat consumer the consumer pays pays in his in orhis her or holdingher holding time. time. They They are discussedare discussed in detail in detail below below and and shown shown in Figure in Figure1. 1.

Product value: Total cost of ownership: Vt() Vt () Vt () PFS TCOt() CtPU () Ct () Ct RA () Rt ()

Funtional Purchase cost, Use cost,

deterioration, VF (t) CP (t) CU (t)

Physical Repair cost, Recycle award,

deterioration, VS (t) CR (t) RA (t)

Consumer value: For different consumer, i Vt() Vt() Pi Ci TCOi () t

Optimal product take-back time

Figure 1. The concept of consumer value. Figure 1. The concept of consumer value. 2.1. Product Value Modeling 2.1. Product Value Modeling According to the work of Kondoh et al. [21], the value of the product deteriorates over time According to the work of Kondoh et al. [21], the value of the product deteriorates over time in in general. The factors that cause this recession can be classiﬁed into functional value deterioration general. The factors that cause this recession can be classified into functional value deterioration and and physical value deterioration. The functional value deteriorates with time due to obsolescence physical value deterioration. The functional value deteriorates with time due to obsolescence resulting from rapid technological innovation and/or changes in market trends. For example, as hard resulting from rapid technological innovation and/or changes in market trends. For example, as hard disk capacity increases, the existing product capacity no longer meets consumers’ expectations. disk capacity increases, the existing product capacity no longer meets consumers’ expectations. The The physical value deterioration may also decrease due to the aging and wearing off of product physical value deterioration may also decrease due to the aging and wearing off of product components. For example, LED screen brightness may fade away and even malfunction with the components. For example, LED screen brightness may fade away and even malfunction with the time. This study employs Equation (1) to model product value (Vp(t)) that incorporates functional time. This study employs Equation (1) to model product value (Vp(t)) that incorporates functional value (VF(t)) deterioration and physical value (VS(t)) deterioration. We use different weightings, wF value (VF(t)) deterioration and physical value (VS(t)) deterioration. We use different weightings, wF and wS, respectively, to denote different ratios for both the functional value and physical value for and wS, respectively, to denote different ratios for both the functional value and physical value for different products. different products. V (t) = ω × V (t) + ω × V (t) P F F S S (1) where ωF + ωS = 1, 0 ≤ ωF, ωS ≤ 1 Sustainability 2017, 9, 385 4 of 17

VtP ()FF Vt ()  SS Vt () Sustainability 2017, 9, 385 4 of(1) 17 where FS1, 0   FS ,  1

Figure 2 below shows that at t = 0, VF(0) and VS(0) are equal to 1 ideally in the beginning. Figure2 below shows that at t = 0, VF(0) and VS(0) are equal to 1 ideally in the beginning. HoweverHowever all valuesvalues decreasedecrease asas timetime goesgoes by.by. TheThe solid lineline representsrepresents thethe productproduct value,value, whenwhen consumers are holding product at time th, the product value is VP(th); when holding time t reaches the consumers are holding product at time th, the product value is VP(th); when holding time t reaches product’s end-of-life, the product value will decrease to VP(tEoL). To note, at the end-of-life point the product’s end-of-life, the product value will decrease to VP(tEoL). To note, at the end-of-life point (tEoL),the product value drops. Henceforth, it represents the lower economic benefit of recovery. The (tEoL), the product value drops. Henceforth, it represents the lower economic benefit of recovery. Theconclusion conclusion can canbe ascertained be ascertained from from the thediagram diagram that that those those who who store store their their unused unused valuable valuable items items at athome home instead instead of recycling of recycling them them not notonly only lose lose the best the besttiming timing to retrieve to retrieve residu residualal profits profits but also but leave also leaveproducts products to decay. to decay. Therefore, Therefore, consumers consumers should should be beencouraged encouraged to torecycle recycle their their products products in anan appropriateappropriate timetime toto improveimprove economiceconomic efficiencyefficiency forfor productproduct recoveryrecoveryand andconsumer consumer value. value.

Product Value,VP ()t

Functional Value Deterioration,VF ()t

Physical Value Deterioration,VS ()t

VtP()h

VP()tEoL

tEoL

Figure 2. The time variation of product value. Figure 2. The time variation of product value.

2.1.1.2.1.1. Functional Value andand PhysicalPhysical ValueValue DeteriorationDeterioration ModelModel ThisThis studystudy modiﬁesmodifies thethe workwork of Yeh [[22]22] andand considersconsiders aa moremore generalgeneral situationsituation toto assumeassume thatthat thethe functionalfunctional valuevalue deteriorationdeterioration modelmodel followsfollows anan exponentialexponential distributiondistribution andand thethe physicalphysical valuevalue deteriorationdeterioration modelmodel followsfollows aa linearlinear distribution,distribution, asas shownshown inin EquationsEquations (2)(2) andand (3),(3), respectively:respectively: XX t Vt() (1X )  e−α×t X ,0  X ,0  t ,0  (2) VF(t)F = (1 − FF) × e + , 0 ≤ X, 0 ≤ t, 0 < α (2) ωF ωF Y Vt() ( 1) t 1, 0Y , 0  t ,0  (3) S YS VS(t) = ( − 1) × β × t + 1, 0 ≤ Y, 0 ≤ t, 0 < β (3) ωS where t denotes holding time counting after the product is bought. VF(0) = VS(0) = 1, VF(∞) = ⁄ where t denotes holding time counting after the product is bought. VF(0) = VS(0) = 1, VF(∞) = X/ωF and VS(tEoL) = ⁄ . ⁄ and ⁄ denote the residual value of the functional performance and and V (t ) = Y/ω . X/ω and Y/ω denote the residual value of the functional performance and the physicalS EoL performance,S Frespectively,S when t approaches ∞ or the time longer enough. Actually, the physical performance, respectively, when t approaches ∞ or the time longer enough. Actually, when the product reaches its end-of-life (tEoL < ∞), its residual value is the material value for recycling. when the product reaches its end-of-life (t < ∞), its residual value is the material value for recycling. The rate of functional value deteriorationEoL is denoted by α, and different products have different α The rate of functional value deterioration is denoted by α, and different products have different α values. When α is greater (such as for a worse performance product, like α3), the value declination is values. When α is greater (such as for a worse performance product, like α ), the value declination greater, otherwise it is lesser, as shown in Figure 3. For the physical value, th3 e rate of physical value is greater, otherwise it is lesser, as shown in Figure3. For the physical value, the rate of physical deterioration is denoted by β, and different groups of users have different β values. For higher value deterioration is denoted by β, and different groups of users have different β values. For higher frequency use persons, who have greater β values (like β3), the value declination is greater and frequency use persons, who have greater β values (like β ), the value declination is greater and products reach their end-of-life earlier. The discussion of α and3 β in detail is shown later. products reach their end-of-life earlier. The discussion of α and β in detail is shown later. Sustainability 2017, 9, 385 5 of 17 Sustainability 2017, 9, 385 5 of 17

123 123

1 1

 2 2

3 3

X Y ωF ωS

(a) (b)

Figure 3. The deterioration rate of functional value and physical value. (a) Functional deterioration, Figure 3. The deterioration rate of functional value and physical value. (a) Functional deterioration, VF(t); (b) Physical deterioration, VS(t). VF(t); (b) Physical deterioration, VS(t). 2.1.2. Modeling the Deterioration Rate of Functional Value 2.1.2. ModelingMany the companies Deterioration (Fujitsu, Rate Mitsubishi, of Functional Hitachi, and Value Toshiba from Japan) have already adopted the Factor X method to assess the degree or rate of progress of a new product. Although the Manycalculations companies of (Fujitsu,the rate are Mitsubishi, different, the Hitachi, concep andt is similar Toshiba and from is used Japan) in evaluating have already product adopted the Factor X methodspecifications to assess to compare the degree the reference or rate ofproduct progress specifications of a new and product. to obtainAlthough the total thefunction calculations of the rate areprogress different, rate theof the concept evaluated is product. similar and is used in evaluating product specifications to compare the reference productFujitsu’s specificationsFactor X method and [23] us toed obtain the root the mean total square function (RMS) progress concept to rate calculate of the the evaluated product product. overall progress ratio; Mitsubishi’s Factor X [24] used the arithmetic mean (average) to calculate the Fujitsu’sproduct Factor overall X method progress [ratio;23] usedand Toshiba’s the root Factor mean Tsquare [25] used (RMS) the quality concept function to calculate deployment the product overall progress(QFD) method ratio; to Mitsubishi’s obtain the weight Factor of user X [demand,24] used then the multiply arithmetic it with mean the specific (average) progress to rate, calculate the product overalland finally progress sum up ratio; the total and value Toshiba’s to get the Factor product T [overall25] used progress the quality ratio. We function modify the deployment Factor T (QFD) method tomethod obtain and the express weight the functional of user demand,deterioration then value multiply in Equation it (4). with Thethe goalspecific of this equation progress is to rate, and obtain the product overall rate of deterioration. finally sum up the total value to get the product overall progress ratio. We modify the Factor T method Evaluated product specifications (old) and express the functionalFunctional deterioration deterioration value value  in Equation (4). The goal ofthis equation(4) is to obtain the product overall rate of deterioration. Reference product specifications (new) The calculation steps of functional deterioration value are the following: Evaluated product specifications (old) (1) Functional Determine a product deterioration to be evaluated value = (Ep) and a product that is comparable to the reference (4) product (Rp). Reference product specifications (new) (2) Identify key specifications of the product (m = 1, 2, …, M). The calculation(3) Choose stepsthe most of significant functional attributes deterioration or functions value for areeach thekey following:specification, then find their performance (Epm is the performance of key specification m of the evaluated product). (1) Determine a product to be evaluated (Ep) and a product that is comparable to the reference (4) Apply the weighting factor () to express the contribution of each key specification. product(5) ( DetermineRp). the key specifications progress vector, when the progress vector goes up, the better (2) Identify keythe performance specifications is; and of use the Equation product (5) to (m find= 1,each 2, attribute’s . . . , M). performance. When the progress vector goes down, use Equation (6) for the calculation, where Rpm is the performance of key (3) Choose the most significant attributes or functions for each key specification, then find their component m of the reference product. performance (Epm is the performance of key specification m of the evaluated product). Multiply the attribute’s performance by the weighting factor and sum the value of the total (4) Applyspecifications the weighting to obtain factor the (totalωm) deterioration to express thevalue contribution of product (Dp of), eachas shown key specification.in Equation (7). (5) DetermineSubstituting the keyDp into specifications Equation (2), we progress can obtain vector, α: when the progress vector goes up, the better the performance is; and use EquationEp (5) to find each attribute’s performance. When the progress Dp  m m Rp (5) vector goes down, use Equation (6)m forfor the case calculation, of larger the where better Rpm is the performance of key component m of the reference product. Multiply the attribute’s performance by the weighting factor and sum the value of the total specifications to obtain the total deterioration value of product (Dp), as shown in Equation (7). Substituting Dp into Equation (2), we can obtain α:

Epm Dpm = for the case of larger the better (5) Rpm

1/Epm Dpm = for the case of smaller the better (6) 1/Rpm Sustainability 2017, 9, 385 6 of 17

M Dp = ∑ Dpm × wm (7) m=1

2.2. Total Cost of Ownership Model The HP Corporation [26] deﬁned TCO to provide the consumer with the direct and indirect cost of IT product evaluation. Ellram [27] indicated that, in general, the TCO of products should include acquisition cost, use cost, maintenance cost, and other relevant costs. This study assumes that the consumer is required to pay the total cost of product, including the product purchase cost, CP, product use cost, CU, product repair cost, CR, and the recycling award, AR. Equation (8) shows the time function of TCO, and each cost will be discussed in the following sub-sections.

TCO(t) = CP(t) + CU(t) + CR(t) − AR(t) (8)

2.2.1. Purchase Cost Modeling

The time function of product purchase cost, CP(t), is the product market value with respect to time. The market value will decrease as the use time of product increases, as shown in Equation (9).

−γ×t CP(t) = P × e (9) where P is the sale price of the product and γ represents the deterioration rate of product price.

2.2.2. Use Cost Modeling We deﬁne the time function of product use cost to be the total cost of electricity consumption under different user scenarios. According to the report of the EuP Lot3 ﬁnal report [28], the consumer use model can be divided into three modes; off (j = 1), sleep (j = 2), and active (j = 3). The off mode is the wattage consumed (kw1) in soft off. The sleep mode is the wattage consumed (kw2) in several low energy consumption states, none of them permitting interactive usage. The active mode is the wattage consumed (kw3) in all power states between idle and high (maximum power usage). The cost of kilowatt hour (kWh) consumption required for mode j at time t, Uj(t), is shown in Equation (10).

Uj(t) = h(t) × rj × kwj × c, for j ∈ {1, 2, 3}, t ≥ 0 (10) where h(t) is the number of hours in t years, rj is the percentage of each mode per year, and c is electricity cost per kWh. The use cost of the consumer is the sum of the cost spent at the three modes, as shown in Equation (11). 3 CU(t) = ∑ Uj(t), t ≥ 0 (11) j=1

2.2.3. Repair Cost Modeling The product repair cost is deﬁned as the cost it takes to repair the product as time passes. We do not consider the product warranty, as shown in Equation (12).

CR(t) = R × f (t) (12) where R is denoted as the total repair cost of the product during the holding time and f is the cumulative failure rate of the product in holding time, and we use a quadratic function of time to simulate it, as shown in Equation (13). f (t) = g × t2 + h × t + v (13) where g and h are coefﬁcients and v is a constant value that we obtain from a curve ﬁtting method. Sustainability 2017, 9, 385 7 of 17

2.2.4. Recycling Awards The product recycling award, which is a function of time, is deﬁned as an award given by the recycler for the used product recycled from the consumer due to the residual value of the used product. Based on the recovery option of the EOL product [29–31], the recovery option can be divided into three recovery types; product reuse, part reuse, and material recycling. Each recovery type could be applied to the Gazelle model on the website [32], where both the length of time used and the current product conditions are considered to estimate the amount of recycling awards, and the result is used as an important reference in this study.

2.3. Consumer Value Assessment Model

Zheithaml [33] deﬁned the value of consumer (Vc) as the consumer’s overall assessment of product utility based on the perceptions of what is received and what is given, as shown in Equation (14). The receipts (Rc) cover functionality, quality, or personal value obtained by the customer and positive feelings sensed by the customer; whereas the contributions (Cc) cover the money, time, or effort given by the customer and negative feelings sensed by the customer.

RC VC = (14) CC In this study, a consumer value assessment model is developed and we deﬁne the product value (VP) obtained by the customer, as shown in Equation (1), as the receipts of the customer, RC. TCO is used to represent customer contribution, CC, as shown in Equation (8). Then the customer value for different consumer use patterns i is a function of time t and can be deﬁned as Equation (15).

VPi(t) VCi(t) = (15) TCOi(t) where VPi(t)represents the value of the product receipt with a different consumer pattern of usage i inholding time t, while TCOi(t) is the total cost of the product contributed. This study explores the value of VCi(t) from the time of the product purchased to determine when is the best time to recycle the product for different use pattern consumers, which can beneﬁt both the customer and the environment.

3. Numerical Illustration To recap from Kwak et al. [6], the typical laptop wear-out lifespan is around 3–5 years, but people tend to keep their laptops for an average storing time of 11 years without using them. The main reason is because notebooks are smaller in size and easier to store. When new replacements are purchased, consumers usually keep the old ones at home instead of recycling them right away. Notebooks have a higher replacement rate, and most of the replaced products are still functional and have high residual values. If the consumer does not recycle her or his product at the right time, then its value will decline over time. It will have negative effects on the economy and the environment. To illustrate the applicability of the proposed model, a simpliﬁed numerical study has been conducted. This study aims to develop a model to help users determine the optimal take-back time. We take notebooks as our research target. The following will explicate the illustration process.

3.1. Description of Evaluated Product and Consumer Groups In this study, the oldest 13.3-inch MacBook Air is used as the evaluated product, and two reference products with the same size are selected as reference products. Table1 indicates the speciﬁcation data of the evaluated product and reference products. Sustainability 2017, 9, 385 8 of 17

Table 1. Product speciﬁcation of evaluated product and reference product [34]. Sustainability 2017, 9, 385 8 of 17

Evaluated Product (EP) Reference Product (RP) Reference Product (RP) Table1. Product specification of evaluated product and reference product [34]. Introduction date 8 June 2009 11 June 2012 9 March 2015

EvaluatedIntel Core Product 2 Duo (E SL9400P) ReferenceIntel Core Product i5-3427U (RP)Intel Reference Core i5-5250U Product (RP) Processor Type (Speed) Introduction date 8 June(1.86 2009 GHz) 11(1.8 June GHz) 2012 (1.6 9 March GHz) 2015 Intel CoreDDR3 2 Duo SDRAM SL9400 2 GB DDR3LIntel Core SDRAM i5-3427U 4 GB DDR3LIntel SDRAM Core i5-5250U 8 GB ProcessorRAM Type Type (Speed) (Speed) (1.86(1066 GHz) MHz) (1600(1.8 GHz) MHz) (1600(1.6 MHz) GHz) DDR3 SDRAM 2 GB DDR3L SDRAM 4 GB DDR3L SDRAM 8 GB RAM TypeVideo (Speed) Card NVIDIA GeForce 9400 M Intel HD 4000 HD Graphics 6000 (1066 MHz) (1600 MHz) (1600 MHz) VideoDisplay Card (Resolution) NVIDIA 13.3” GeForce (1280 9400× 800 M ) 13.3” Intel (1440 HD ×4000900 ) 13.3” HD (1440 Graphics× 900 6000 ) Display (Resolution)Hard Drive 13.3 120″ (1280 GB (4200× 800 RPM)) 13.3 256″ (1440 GB SSD× 900 ) 25613.3″ GB (1440 SSD × 900 ) Hard DriveUSB Ports 120 GB (4200 1 (USB RPM) 2.0) 256 2 (USB GB SSD 3.0) 2 (USB 256 GB 3.0) SSD USB Ports 1 (USB 2.0) 2 (USB 3.0) 2 (USB 3.0) Battery life 5 h 7 h 12 h Battery life 5 h 7 h 12 h DimensionsDimensions (H × (HW × D)W × D) 1.94 1.94 × 32.5× 32.5× 22.7× (cm)22.7 (cm) 1.7 1.7× × 32.5 × 22.722.7 (cm) (cm) 0.68 0.68× 12.8 × 12.8× 8.94× 8.94 (cm) (cm) SystemSystem Weight Weight 1.36 1.36kg kg 1.35 kg 1.35 1.35 kg kg OriginalOriginal Price Price US$1299 US$1299 US$1299 US$1199 US$1199

According to the EuP Lot3 investigation report, there are two types of consumer product usage According to the EuP Lot3 investigation report, there are two types of consumer product usage patterns; an office use pattern and a home use pattern [28]. In this study, we add two more usage patterns; an ofﬁce use pattern and a home use pattern [28]. In this study, we add two more usage patterns an always use pattern as the upper bound and a ‘seldom use’ pattern as the lower bound of patterns an always use pattern as the upper bound and a ‘seldom use’ pattern as the lower bound the usage patterns. We explore the consumer value and optimal product take-back time for four of the usage patterns. We explore the consumer value and optimal product take-back time for four different consumer groups and show each usage pattern as a percentage of the number of hours per different consumer groups and show each usage pattern as a percentage of the number of hours per year in Figure 4. The ‘always use’ customers spend 5840 h (67%) in the active mode and 2920 h (33%) year in Figure4. The ‘always use’ customers spend 5840 h (67%) in the active mode and 2920 h (33%) in the sleep mode, and these two modes totally cover the hours in a year (8760 h); namely, they leave in the sleep mode, and these two modes totally cover the hours in a year (8760 h); namely, they leave the computer powered on all the time. The ‘seldom use’ customers spend 876 h (10%) in the active the computer powered on all the time. The ‘seldom use’ customers spend 876 h (10%) in the active mode, 1752 h (20%) in the sleep mode, and 6132 h (70%) in the off mode; namely, they let the computer mode, 1752 h (20%) in the sleep mode, and 6132 h (70%) in the off mode; namely, they let the computer power off most of time and only use the computer 10% of the whole time. power off most of time and only use the computer 10% of the whole time.

Figure 4. Product usage patterns of the notebook computer.

3.2. Calculation of Product Value Base on the data shown in Figure 4 4,, inin thisthis example,example, thethe useuse frequencyfrequency percentagespercentages ofof thethe productproduct forfor thethe alwaysalways useuse ((FF11), use inin thethe ofﬁceoffice ((FF22), use atat homehome ((FF33), and seldom useuse ((F44) patterns are set to 100%,100%, 64%,64%, 49%,49%, andand 30%,30%, respectively.respectively. The functional deterioration value over time is obtained by the Factor T that we modified, as shown in Table 2; here the key specification items are based on a consumer survey report from the Market Intelligence and Consulting Institute [35]. Nine elements to which consumers pay more attention in terms of product specifications were identified as the key specifications of notebooks; they are Processor/RAM, Video Card, Display, Hard drive, USB ports, Battery, Dimensions, and Sustainability 2017, 9, 385 9 of 17

SustainabilityThe 2017 functional, 9, 385 deterioration value over time is obtained by the Factor T that we modified,9 of 17 as shown in Table2; here the key specification items are based on a consumer survey report from the Weight. The last two specifications are smaller for having better performance; the others are the Market Intelligence and Consulting Institute [35]. Nine elements to which consumers pay more opposite. Using Equations (5)–(7), we can obtain that the functional deterioration value of the attention in terms of product specifications were identified as the key specifications of notebooks; evaluated product declines from 1 to 0.508 after 3 years and to 0.262 after 6 years. Use Equation (2) to they are Processor/RAM, Video Card, Display, Hard drive, USB ports, Battery, Dimensions, and obtain the functional deterioration value rate, α, which is 0.225. Figure 5 shows the curve of the Weight. The last two specifications are smaller for having better performance; the others are the product functional deterioration. opposite. Using Equations (5)–(7), we can obtain that the functional deterioration value of the evaluated product declines from 1 toTable 0.508 2.after Value 3 of years overall and functional to 0.262 deterioration. after 6 years. Use Equation (2) to obtain the functional deterioration value rate, α, which is 0.225. Figure5 shows the curve of the product functionalSpecifications deterioration. Performance Unit Epm Rpm Dpm Wm CPU/RAM Geekbench Performance 1 Score↑ 2701 6757 0.40 0.34 Graphic Card PassMarkTable G3D 2. RatingValue of2 overallScore functional↑ deterioration.124 474 0.26 0.13 Display Resolution Pixel↑ 1,024,000 1,296,000 0.79 0.17 HardSpecifications Drive PassMark Performance Disk Rating 3 UnitGB↑ Epm 181 Rpm 3887 Dpm 0.05 Wm0.09 USB PortsCPU/RAM DateGeekbench Transfer Performance Speed 1 Score Gbps↑ ↑ 27010.96 6757 10 0.40 0.10 0.340.01 BatteryGraphic Card PassMarkMax. Battery G3D Life Rating 2 ScoreHours↑ ↑ 1245 474 7 0.260.71 0.130.15 DimensionsDisplay Max. Resolution High Pixel Cm↑ ↓ 1,024,0001.94 1,296,000 1.7 0.790.88 0.170.03 Hard Drive PassMark Disk Rating 3 GB↑ 181 3887 0.05 0.09 Weight Avg. Weight Kg↓ 1.36 1.35 0.99 0.09 USB Ports Date Transfer Speed Gbps↑ 0.96 10 0.10 0.01 1 GeekbenchBattery uses a number Max. of diffe Batteryrent Life benchmarks Hours to measure↑ 5performance, 7 which 0.71included Integer 0.15 Performance,Dimensions Loathing Point Max. Performance, High Memo Cmry ↓Performance,1.94 and Stream 1.7 Performance 0.88 [36]; 0.03 2 Weight Avg. Weight Kg↓ 1.36 1.35 0.99 0.09 G3D Rating conducts three different tests and then averages the results together to determine the 1 PassMarkGeekbench 3D usesMark a numberfor a system of different [37]; 3 benchmarks Disk rating to conducts measure performance,three different which tests, included Disk Sequential Integer Performance, Read, Loathing Point Performance, Memory Performance, and Stream Performance [36]; 2 G3D Rating conducts three Diskdifferent Sequential tests and Write, then averages and Disk the resultsRandom together Seek to RW, determine and finally the PassMark averages 3D Mark the forresults a system together [37]; 3 Diskto determinerating conducts the PassMark three different Disk tests, Mark Disk for Sequential a system. Read, Disk Sequential Write, and Disk Random Seek RW, and finally averages the results together to determine the PassMark Disk Mark for a system.

Figure 5. Functional deterioration value rate, α. Figure 5. Functional deterioration value rate, α. According to are port from Apple [38], the average physical life of a notebook computer is 7 years,According and we to takeare port this datafrom toApple project [38], other the consumeraverage physical groups’ life average of a notebook physical life;computer always is use7 years,(N1), and use we in thetake ofﬁce this data (N2), to use project at home( otherN co3),nsumer and seldom groups’ use average (N4) are physical set to 4.5, life; 6.3, always 8, and use 12 ( years,N1), userespectively. in the office The (N rates2), use of physicalat home( valueN3), and deterioration, seldom useβ, discussed(N4) are set in Equationto 4.5, 6.3, (3) 8, can and be 12 calculated years, respectively.from Equation The (16),rates which of physical are 0.222, value 0.101, deterioration, 0.061, and β 0.025,, discussed respectively, in Equation for the (3) differentcan be calculated consumer fromgroups. Equation The notebook(16), which computer are 0.222, product 0.101, 0.061, value and of different 0.025, respectively, consumer groupsfor the withdifferent holding consumer time is groups.shown The in Figure notebook6. With computer an increase product in the value frequency of different of use, consumer the value groups of the product with holding decreases time over is showntime. in When Figure the 6. holding With an time increase reaches in the productsfrequency maximum of use, the physical value of life the (lifespan), product decreases the value over of the time.product When will the become holding stagnant. time reaches the products maximum physical life (lifespan), the value of the F product will become stagnant. β = (16) N F   (16) N Sustainability 2017, 9, 385 10 of 17 Sustainability 2017, 9, 385 10 of 17

Figure 6. The product value for various consumer groups. Figure 6. The product value for various consumer groups. 3.3. Calculation of TCO 3.3. Calculation of TCO 3.3.1. Purchase, Use, and Repair cost 3.3.1. Purchase, Use, and Repair cost Cost The product purchase cost of a notebook, P, is the price as shown on Apple’s official website [34] and isThe assumed product to purchase be P = US$1299. cost of a notebook, Figure 7 shows P, is the the price price holding as as shown shown value on on of A Apple’sdifferentpple’s official ofﬁcial consumer website groups [34] [34] andover is time. assumed When to the be frequencyP = US$1299. of useFigure increases, 77 showsshows the thethe amortization holdingholding valuevalue cost ofof increases differentdifferent consumerwithconsumer time groupsandgroups the overmarket time. value When When decreases the the frequency with time. of of use increases, the amortization cost increases with time and the market value decreases with time.

Figure 7. The purchase cost varies over timetime for various consumer groups. Figure 7. The purchase cost varies over time for various consumer groups. Based on the the data data from from the the International International Energy Energy Agency Agency (IEA) (IEA) [39], [39 in], inEquation Equation (11) (11) wewe use use c = cUS$0.125= US$0.125Based /KWh on /KWh the for data thefor thepricefrom price ofthe electricity of International electricity in inUSA. USA.Energy The The averageAgency average power(IEA) power [39], consumption consumption in Equation for for (11)each each we operation operation use c = US$0.125mode and /KWh the annual for the powerpower price of consumptionconsumption electricity in costcost USA. ofof The differentdifferent average consumerconsumer power consumption groupsgroups areare shownshown for each inin TableoperationTable3 .3. mode and the annual power consumption cost of different consumer groups are shown in Table 3. Table 3.3. Power consumption forfor thethe evaluatedevaluated product.product. Table 3. Power consumption for the evaluated product. Operational Electricity Annual Power Consumption Cost (US$) Operational Electricity Annual Power Consumption Cost (US$) OperationalModes UsedElectricity (kW) * Always UseAnnual OfficePower Use Consumption Home Cost Use (US$) Seldom Use Modes Used (kW) * Always Use Ofﬁce Use Home Use Seldom Use OffModes (kW1) Used 0.00056 (kW) * Always 0 Use Office 0.176 Use Home 0.250 Use Seldom 0.441 Use OffSleepOff (kW1) (kW1) (kW2) 0.000560.00056 0.00102 0 0.327 0 0.1760.176 0.335 0.2500.250 0.325 0.441 0.0490.441 Sleep (kW2) 0.00102 0.327 0.335 0.325 0.049 ActiveSleep (kW2) (kW3) 0.00102 0.0131 0.3277.708 0.3353.449 0.3251.832 0.0490.576 Active (kW3) 0.0131 7.708 3.449 1.832 0.576 Total ------8.035 3.961 2.407 1.068 ActiveTotal (kW3) ------0.0131 8.035 7.708 3.961 3.449 2.407 1.832 0.576 1.068 Total ------8.035 3.961 2.407 1.068 Sustainability 2017, 9, 385 11 of 17 SustainabilitySustainability 20172017,, 99,, 385385 1111 ofof 1717

Moreover,Moreover, assumeassume thatthat thethe averageaverage maintenancemaintenance fee,fee, RR,, ofof aa notebooknotebook computercomputer isis US$175US$175 withinwithin Moreover, assume that the average maintenance fee, R, of a notebook computer is US$175 within thethe product’sproduct’s cyclecycle life.life. OnOn thethe otherother hand,hand, thethe survsurveyey byby thethe notebooknotebook computercomputer warrantywarranty providerprovider the product’s cycle life. On the other hand, the survey by the notebook computer warranty provider SquareSquare TradeTrade [40][40] inin AmericaAmerica indicatesindicates thatthat thethe malfmalfunctionunction raterate ofof thethe evaluatedevaluated productproduct inin thethe firstfirst Square Trade [40] in America indicates that the malfunction rate of the evaluated product in the ﬁrst yearyear isis 5.8%,5.8%, andand thisthis goesgoes upup toto 25.1%25.1% afterafter usingusing thethe computercomputer forfor 33 years.years. TheThe componentscomponents likelike year is 5.8%, and this goes up to 25.1% after using the computer for 3 years. The components like keyboards,keyboards, pointerpointer devices,devices, mediamedia drives,drives, andand hardhard drivesdrives areare allall mechanicalmechanical componentscomponents thatthat wearwear keyboards, pointer devices, media drives, and hard drives are all mechanical components that wear outout whenwhen subjectedsubjected toto heavyheavy use.use. AsAs aa resultresult,, wewe determinedetermine thethe malfunctionmalfunction raterate curve,curve, ff((tt),), byby curvecurve out when subjected to heavy use. As a result, we determine the malfunction rate curve, f (t), by curve fitting.fitting. InIn thethe casecase ofof thethe homehome useuse model,model, thethe acaccumulativecumulative malfunctionmalfunction raterate willwill bebe 100%100% whenwhen thethe ﬁtting. In the case of the home use model, the accumulative malfunction rate will be 100% when the productproduct usedused forfor 77 years,years, asas shownshown inin FigureFigure 8.8. product used for 7 years, as shown in Figure8.

FigureFigure 8.8. AccumulativeAccumulative malfunction malfunction raterate overover time.time.

P U FigureFigure9 99 presents presentspresents the thethe time timetime variation variationvariation value valuevalue for forfor the thethe purchase purchasepurchase cost costcost ( (C(CCPP((tt)),)), useuse costcost ((CCUU((tt)))) and and repair repair R P costcost ((CCRR((tt)))) forfor thethe differentdifferent consumer consumer groups. groups. CCPP((tt)) isis aa a decreasingdecreasing decreasing functionfunction with with respect respect to toto time, time, while while U R CCUU((tt)) is is a aa horizontal horizontal straight straight line line and and CCRR((tt)) is is an an increasing increasing function. function. The aggregate effects of of thesethese threethree costscostscosts form formform a aa concave concaveconcave function. function.function. As AsAs the thethe frequency frequefrequencyncy of usageofof usageusage increases, increases,increases, the amortizationthethe amortizationamortization for the forforC thePthe(t) P P willCCP((tt)) increase willwill increaseincrease relatively, relatively,relatively, and the andand declining thethe decliningdeclining rate of raterate the ofofCP thethe(t) isCC fasterP((tt)) isis fasterfaster than the thanthan increasing thethe increasingincreasing rate of raterate the ofofC R thethe(t). R P U R AsCCR((t at).).result, AsAs aa result,result, the lowest thethe lowestlowest point pointpoint of the ofof curve thethe curvecurve of C ofofP( t CC)P +((tt)C) ++U CC(tU)(( +tt)) C++ RCC(Rt()(tt) (concave) (concave(concave function) function)function) will willwill bebebe reachedreached earlierearlier as as the the frequency frequency ofof usageusage increasesincreases more.more.

FigureFigure 9. 9. TheThe purchase, purchase, use, use, and and repair repair costs costs change change overover timetime forfor variousvarious consumerconsumer groups.groups.

Sustainability 2017, 9, 385 12 of 17 Sustainability 2017, 9, 385 12 of 17 3.3.2. Recycling Award 3.3.2.Different Recycling countries Award may have different recycling award regulations for returned products (cores). Consumers could negotiate the award money with the recyclers through market mechanisms. (cores).Different Consumers countries could may negotiate have different the award recycling money awardwith the regulations recyclers thro for returnedugh market products mechanisms. (cores). Basically, there are two kinds of recycling award scenarios; Scenario 1 assumes that the recycling ConsumersBasically, there could are negotiate two kinds the awardof recycling money award with the scenarios; recyclers Scenario through market1 assumes mechanisms. that the recycling Basically, award is fixed no matter how good the product condition is or whether its age is young or old, thereaward are is twofixed kinds no matter of recycling how awardgood the scenarios; product Scenario condition 1 assumes is or whether that the its recycling age is young award isor ﬁxed old, whereas Scenario 2 assumes variable recycling awards, namely, different awards for products with nowhereas matter Scenario how good 2 assumes the product variable condition recycling is or awar whetherds, namely, its age isdifferent young orawards old, whereas for products Scenario with 2 different conditions and ages. For the fixed recycling award scenario, it reduces recycling incentives assumesdifferent variableconditions recycling and ages. awards, For the namely, fixed recycling different award awards scenario, for products it reduces with differentrecycling conditionsincentives and leads to the result that the consumers tend to store their products, even if they no longer use and ages.leads Forto the the result ﬁxed recyclingthat the consumers award scenario, tend itto reduces store their recycling products, incentives even andif they leads no to longer the result use them. Figure 10 shows a recycling award, AR, for two recycling award scenarios, and the data are thatthem. the Figure consumers 10 shows tend a torecycling store their award, products, AR, for even two ifrecycling they no longeraward usescenarios, them. and Figure the 10 data shows are adopted from the Gazelle website[32]. We will investigate the relationship between the recycling aadopted recycling from award, the AGazelleR, for twowebsite[32]. recycling We award will scenarios, investigate and the the relationship data are adopted between from the the recycling Gazelle awards and the consumer values by comparing the results of these two scenarios in the following websiteawards and [32]. the We consumer will investigate values theby comparing relationship the between results theof these recycling two awardsscenarios and in thethe consumerfollowing section. valuessection. by comparing the results of these two scenarios in the following section.

Figure 10. Recycling award, AR, for two recycling award scenarios. Figure 10. Recycling award, AR,, for for two two recycling recycling award scenarios.

In the fixed recycling award scenario, TCO behaves similarly to CP(t) + CU(t) + CR(t) in Figure 9, In the fixed recycling award scenario, TCO behaves similarly to CP(t) + CU(t) + CR(t) in Figure9, and the lowest point of the curve of TCO is reached earlier as the frequency of usage increases more, and the lowest point of the curve of TCO is reached earlier as the frequency of usage increases more, as shown in Figure 11. In the variable recycling award scenario, the product groups of always used, as shown in Figure 11. In the variable recycling award scenario, the product groups of always used, used in the office, used at home, and seldom used have their lowest TCO at the holding time of 2.55, used in the office, used at home, and seldom used have their lowest TCO at the holding time of 2.55, 3.47, 4.36, and 5.46 years, respectively. With a higher frequency of use, the greater is the decline of 3.47, 4.36, and 5.46 years, respectively. With a higher frequency of use, the greater is the decline of TCO compared with the fixed recycling awards scenario. This is because the variable recycling award TCO compared with the fixed recycling awards scenario. This is because the variable recycling award is a decreasing function over time; the earlier the consumer recycles her or his product, the higher is is a decreasing function over time; the earlier the consumer recycles her or his product, the higher is the award. the award.

Figure 11. Total cost of ownership (TCO) for various consumer groups with two recycling award scenarios. Figure 11. Total cost of ownership (TCO) for various consumer groups with two recycling award scenarios. Sustainability 2017, 9, 385 13 of 17

3.4. Optimal Take-Back Time of Product In this study, the Maple 13 software is used for optimization. Figure 12 shows the consumer value of four consumer groups with fixed and variable recycling award scenarios. With a higher frequency of use, the highest point of the VC(t) occurs earlier for both scenarios. In the variable scenario, each consumer group also attains a higher consumer value in advance compared with the fixed scenario, and this scenario will motivate the customers to recycle their unused products as soon as possible. 0 In order to understand consumer value better, this study defines relative consumer value, VCi (t), for use group i, as shown in Equation (17), which uses the initial consumer value (VCi(0)) as a reference to calculate the ratio of VCi(t) to VCi(0).

0 VCi(t) VCi (t) = for group i (17) VCi(0)

0 0 where VCi (0) = 1. When VCi (t) is greater than 1, it represents how much the consumer value increases compared with the initial consumer value. 0 0 Figure 13 shows that VCi (t) increases from VCi (0)then reaches its maximum value at T1. After it 0 reaches the maximum value, it starts to go down to reach VCi (0) again at T2, then its value will keep going down and the value becomes less than 1. Except for the seldom use group, all other groups behave similarly, as described above, for both recycling award scenarios. For the variable recycling award scenario, all use groups have higher maximum relative consumer value and shorter T1 and T2 compared with the ﬁxed recycling award scenario, as shown in Figure 13 and Table4. Since at T1, the customer has maximum consumer value and at T2 the customer value goes back to its initial consumer value, this study suggests that the customer can take T1 and T2 as important factors to determine the optimal take-back time. For the customer that likes to use new (or like new) products all the time, she or he can choose T1 to recycle his product; the ordinary customer can choose T2 (or 0 0 an approximate time) to recycle their product. Table4 demonstrates VCi (T1) and VCi (T2) for various usage patterns in two recycling award scenarios and illustrates that those use groups with a higher frequency of use have shorter value for T1 and T2 and a higher value for maximum consumer value. Under fixed recycle awards scenarios, the take-back times for always users, office users, and home users are 4.11, 5.08, and 5.25 years, respectively. On the other hand, under variable recycle awards scenarios, we offer higher awards to those who recycle their products earlier. Therefore, there is a significant change on the optimal take-back time; 3.72 years, 4.59 years, and 4.93 years, respectively. The results imply that the variable recycling award scenario is a better strategy than the fixed recycling award scenario. Moreover, it encourages the consumers to recycle their products in advance when they no longer use them. Different usage frequency groups have different best timing to recycle their products. For the customers in the seldom use group, the results suggest that it is better for them to recycle their product right after they have bought the product; namely, they do not need to buy the product or they can rent the product.

Table 4. Relative customer value and take-back time for various consumer groups with two recycling

award scenarios. (Unit of T1 and T2: Year).

Fixed Scenario Variable Scenario Difference T (V 0) 2.37 (1.63) 2.04 (2.32) −0.33 (+42%) Always Use 1 Ci 4.11 3.72 −0.39 T (V 0) 2.96 (1.45) 2.57 (1.86) −0.39 (+28%) Ofﬁce Use 1 Ci T2 5.08 4.59 −0.49 T (V 0) 3.04 (1.21) 2.80 (1.42) −0.24 (+17%) Home Use 1 Ci T2 5.25 4.93 −0.32 T (V 0) 0 (1) 0 (1) 0 (+0%) Seldom Use 1 Ci T2 0 0 0 0 Maximum consumer value occurs at T1, consumer value goes back to VCi (0) at T2. SustainabilitySustainability 20172017,, 99,, 385385 14 of 17 Sustainability 2017, 9, 385 14 of 17

Figure 12. The consumer value for various consumer groups with two recycling award scenarios. FigureFigure 12. 12. TheThe consumer consumer value value for for various various consumer consumer gr groupsoups with with two two recyc recyclingling award award scenarios. scenarios.

Figure 13. Optimal take-back time of the product for different consumer groups with two recycling Figure 13. Optimal take-back time of the product for different consumer groups with two recycling awardFigure scenarios.13. Optimal take-back time of the product for different consumer groups with two recycling award scenarios. award scenarios. 4. Conclusions 4. Conclusions The study study proposed proposed a aconsumer consumer value value assessment assessment mo model,del, which which is a function is a function of time, of time,and could and The study proposed a consumer value assessment model, which is a function of time, and could couldhelp consumers help consumers to understand to understand how how value value changes changes during during the the holding holding period period and and to to determine help consumers to understand how value changes during the holding period and to determine whetherwhether thethe productproduct is is worth worth keeping keeping or or should should be recycled.be recycled. The The optimal optimal product product take-back take-back time withtime whether the product is worth keeping or should be recycled. The optimal product take-back time considerationwith consideration of consumer of consumer value value can becan determined be determined when when the consumerthe consumer value value decreases decreases below below its with consideration of consumer value can be determined when the consumer value decreases below originalits original value value and and when when the costthe cost of consumers of consumer keepings keeping the product the product exceeds exceeds the value the receiptedvalue receipted and it its original value and when the cost of consumers keeping the product exceeds the value receipted isand no it longer is no longer worth worth keeping keeping for economic for economic benefit. benefit. and it is no longer worth keeping for economic benefit. The studystudy foundfound thatthat there there are are two two main main factors factor affectings affecting the the optimal optimal take-back take-back time; time; namely, namely, the The study found that there are two main factors affecting the optimal take-back time; namely, usagethe usage hours hours oflaptop of laptop and and the the recycling recycling award award of of used used products. products. There There are are two two differentdifferent recyclingrecycling the usage hours of laptop and the recycling award of used products. There are two different recycling award schemes,schemes, fixedfixed andand variablevariable recyclingrecycling awards.awards. A fixedfixed recycling award, executed in mostmost award schemes, fixed and variable recycling awards. A fixed recycling award, executed in most countries, only gives a fixedfixed amount of award forfor recycling, whichwhich doesdoes notnot considerconsider the quality and countries, only gives a fixed amount of award for recycling, which does not consider the quality and lifelife ofof thethe usedused products.products. This award offersoffers anan insufficientinsufficient amountamount ofof incentiveincentive andand cannotcannot induceinduce life of the used products. This award offers an insufficient amount of incentive and cannot induce consumers to recycle laptops that are no longer in use, whereas, with a variable recycling award, consumers to recycle laptops that are no longer in use, whereas, with a variable recycling award, consumers could become more willing to recycle the used product at an earlier time to receive a better consumers could become more willing to recycle the used product at an earlier time to receive a better Sustainability 2017, 9, 385 15 of 17 consumers could become more willing to recycle the used product at an earlier time to receive a better award. This variable award scheme can promote higher product residual values as social resource use and can reduce the negative impact on the environment. It is highly suggested to governments for their policy making in future. We believe that the result of this study can help consumers to calculate the optimal take-back time for their product as well as the consumer value when they input their product specifications and conditions. In addition, the result enables consumers to compare different products in the same category for a reference of future purchase. Upon data mining with the offered information, we expect that manufacturers may exploit environmentally friendly products that possess higher consumer value. Although this study has taken care of many issues, there is still more research needed. For example, an extension of our model can be applied to different brands or types of laptop or even different products. Moreover, the effects of government subsidy on different recycling award schemes are also interesting to study.

Acknowledgments: This work is supported in part by the Ministry of Science and Technology of Republic of China under the grant MOST 105-2221-E-033-044. Author Contributions: Both authors designed the research and wrote the paper. Yi-Tse Fang collected and analyzed the data. Hsin Rau controlled the quality assurance. Conﬂicts of Interest: The authors declare no conﬂict of interest.

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