《Did I Buy the Wrong Gadget? How the Evaluability of Technology Features Influences Technology Feature Preferences and Subsequent Product Choice》中英文對比文獻翻譯

• Abstract
• 摘要：
• 1.Introduction
• 1.引言
• 2.Literature Review and Hypotheses Development
• 2.文獻回顧與假設發展
• 3.Methodology and Results
• 3.方法與結果
• • 3.1Exploratory Pilot Studies
  • 3.1探索試點研究
  • 3.2 Experiment 1
  • 3.2實驗1
  • 3.3Experiment 2
  • 3.3實驗2
• 4.Discussion
• 4.討論
• 5.Theoretical Contributions
• 5.理論貢獻
• 6.Practical Contributions
• 6.實際貢獻
• 7.Limitations and Opportunities for Future Studies
• 7.局限性和未來研究方向
• 8.Conclusion
• 8.結論

引用：Valacich J S , Wang X , Jessup L M . Did I Buy the Wrong Gadget? How the Evaluability of Technology Features Influences Technology Feature Preferences and Subsequent Product Choice[J]. MIS Quarterly, 2018, 42(1):633-644.

Abstract

Prior usability assessment research has paid little attention to how product and feature ratings are influenced by the evaluation context. However, the evaluability hypothesis, which guides this research, suggests that the evaluation context is a vital factor in shaping user’s assessments and perceptions about technology features. pacifically, the evaluability hypothesis proposes that technology feature perceptions, and ultimately technology choices, will change when evaluating a single technology in isolation versus when simultaneously comparing more than one. To demonstrate the evaluability hypothesis effect in the context of consumer technology product evaluations, two experiments were conducted. Both studies support the evaluability hypothesis effect, showing that when two IT products are compared, hard-to-evaluate but easy-to-compare features are perceived to be more important and therefore have a larger influence on product preferences. Alternatively, when evaluating a single product in isolation, easy-to-evaluate features are perceived to be more important and therefore have a larger influence on product preferences. Consequently, different product preferences emerge (i.e., preference reversals) in different evaluation contexts. The results demonstrate that this theoretical lens is robust to the technology evaluation context, providing important theoretical and practical insights for technology design, usability assessments, and, ultimately, product acceptance.

摘要：

之前的可用性評估研究很少關注評估環境如何影響產品和特性評估。然而，指導這項研究的可評估性假設表明，評估環境是形成用戶對技術特性的評估和感知的重要因素。具體來說，可評估性假說提出，當單獨評估一項技術時，與同時比較多項技術時相比，技術特征感知以及最終的技術選擇將發生變化。為了驗證消費者技術產品評估中的可評估性假設的影響，我們進行了兩個實驗。這兩項研究都同意可評估性假設的影響，表明當兩個IT產品進行比較時，難以評估但易于比較的特征被認為更重要，因此對產品偏好的影響更大。另外，當單獨評估一個產品時，容易評估的特性被認為更重要，因此對產品偏好有更大的影響。因此，在不同的評估環境中會出現不同的產品偏好（即偏好逆轉）。結果表明，該理論視角對技術評估環境具有很強的作用，為技術設計、可用性評估以及最終的產品接受度提供了重要的理論和實踐見解。

1.Introduction

Guided by research and practice in human–computer interaction (HCI), technology designers pursue high usability, which depends on technology attribute categories such as content, ease of use, and promotion (Agarwal and Venkatesh 2002). To achieve high usability, designers often conduct evaluations to examine the relative importance of various technology features (Benlian and Hess 2011; Keil and Tiwana 2006). However, because people often have different preferences for technology features in different evaluation contexts (Valacich et al. 2007), understanding the context of a product’s evaluation is an important part of the usability assessment process. For example, if a user perceives the Fitbit Alta to have better social media support than the Nike FuelBand, a person most interested in using social media to share exercise updates with friends may prefer the Alta, which provides strong features to support social activities including leaderboards, status updates, automatic posts to Facebook, and so on. Alternatively, if another person perceives the Nike FuelBand to have greater movement tracking accuracy than the Alta, a person most interested in activity tracking accuracy would likely prefer the FuelBand (all other things being equal).

1.引言

在人機交互（HCI）的研究和實踐的指導下，技術設計師追求高可用性，這取決于諸如內容，易用性和推廣等的技術屬性類別（Agarwal和Venkatesh 2002）。為了實現高可用性，設計人員經常進行評估，以檢驗各種技術特性的相對重要性（Benlian和Hess，2011； Keil和Tiwana，2006）。然而，由于人們在不同的評估環境中對技術特性有不同的偏好(Valacich et al. 2007)，了解產品評估的環境是可用性評估過程中的重要部分。例如，如果用戶認為Fitbit Alta比Nike FuelBand具有更好的社交媒體支持，那么最有興趣使用社交媒體與朋友分享鍛煉最新信息的人可能會喜歡Alta，它提供強大的功能來支持包括排行榜的社交活動，狀態更新，自動發布到Facebook等。或者，如果另一個人認為Nike FuelBand具有比Alta更高的運動跟蹤精度，那么對活動跟蹤精度最感興趣的人可能會更喜歡FuelBand（在所有其他條件相同的情況下）。

Another important contextual factor influencing usability evaluations relates to whether a person is considering a product in isolation (e.g., “Should I buy a Fitbit?”) or comparing multiple products, which is often the case in more mature product categories (e.g., “Do I like Fitbit Alta or Nike FuelBand?”). As such, it is possible that people may perceive one technology feature highly important when considering a single technology in isolation, but may not value that feature as much when simultaneously comparing multiple IT products. This issue is further exacerbated given that multiple generations of products frequently coexist in the market (Xu et al. 2010). Consequently, designers must consider various contextual factors (e.g., isolated evaluation, product comparison, primary use) when assessing product features or else misleading evaluations may occur, leading to costly errors in the design, production, and marketing of products.
影響可用性評估的另一個重要的環境因素涉及到一個人是否在單獨考慮一個產品(例如，“我應該買一個Fitbit嗎?”)或比較多個產品，這種情況通常出現在更成熟的產品類別(例如，“我喜歡Fitbit Alta還是Nike FuelBand?”) 因此，在單獨考慮單個技術時，人們可能會認為一個技術特性非常重要，但是在同時比較多個it產品時，可能不會那么重視該特性。這個問題進一步惡化了，因為在市場上，多代產品經常共存(Xu et al. 2010)。因此，設計師在評估產品特性時必須考慮各種環境因素(例如，孤立的評價、產品比較、主要用途)，否則可能會產生誤導性的評價，導致產品在設計、生產和營銷中出現代價高昂的錯誤。

Prior research on technology adoption has focused primarily on identifying various factors, such as technology features, that influence why individuals adopt a single technology (Venkatesh et al. 2003; Venkatesh, Thong and Xia 2012; Venkatesh et al. 2016; Wixom and Todd 2005). Relatively little is known, however, regarding how people evaluate technology when more than one product option is being considered. Examining how technologies are evaluated in different contexts can extend the prior research on HCI design, usability, and technology adoption. To address these gaps, our guiding research question is: Does the relative importance of the technology features influencing an IT product evaluation change when evaluating a single product in isolation versus when evaluating two products in comparison?
先前對技術采用的研究主要集中在確定影響個人采用單一技術的原因的各種因素（例如技術特性）（Venkatesh等人，2003； Venkatesh，Thong和Xia，2012； Venkatesh等，2016； Wixom和Todd，2005）。 ）。然而，關于人們在考慮多種產品選擇時如何評價技術，人們所知相對較少。研究如何在不同的環境中評估技術，可以擴展之前關于HCI設計、可用性和技術采用的研究。為了解決這些差距，我們的指導研究問題是:在單獨評估單個產品時，與在比較中評估兩個產品時，影響IT產品評估的技術特性的相對重要性是否會發生變化?

To understand how people’s preference toward technology features and subsequent product evaluation differ when making an isolated evaluation versus when comparing multiple products, we draw upon the evaluability hypothesis (EH) (Hsee 1996; Hsee et al. 1999; Hsee et al. 2013). The EH suggests that when evaluating a product in isolation, people tend to perceive easy-to-evaluate features (e.g., aesthetics2) as being more important and therefore more heavily consider those features. However, when simultaneously comparing multiple products, people tend to perceive features that are hard to evaluate in isolation, but easy to compare (e.g., screen resolution), as being more important and therefore more heavily consider those features. Consequently, when a product is being assessed in isolation versus when being compared to another, different technology feature, preferences can emerge. To explore the EH within the context of IT-based consumer products, we report two experimental studies.
為了了解人們對技術特性和后續產品評價的偏好在進行單獨評價和比較多個產品時的差異，我們采用了可評估性假設（EH）（Hsee 1996; Hsee et al。1999; Hsee et al。2013）。EH表明，當單獨評估一個產品時，人們傾向于將易于評估的功能(如審美)視為更重要的特性，因此更重視這些特征。然而，當同時比較多個產品時，人們傾向于認為很難單獨評估但容易比較的特性(如屏幕分辨率)更重要，因此更重視這些特性。因此，當單獨評估一個產品和與其它產品對比評估的情況出現時，對于不同的技術特性，可能會出現偏好。為了在基于IT的消費品環境中探索EH，我們報告了兩個實驗研究。

Our work makes two important contributions. First, we contribute to the existing HCI and usability literature by highlighting how differences in the evaluation context can shape assessments and outcomes. Specifically, we show that people’s preferences toward technology features differ when considering a single product in isolation versus when considering two products in comparison. This in turn helps us provide important practical guidelines for IT design. Second, our work contributes to the existing technology adoption literature by demonstrating how IT product evaluation and preferences change in different contexts. The implications of our research for the broader technology adoption literature could be profound, providing both an important boundary condition for existing theoretical perspectives and methodological insights for the design of future studies.
我們的工作做出了兩個重要貢獻。首先，我們通過強調評估環境中的差異如何影響評估和結果，為現有的HCI和可用性文獻做出貢獻。具體地說，我們表明，人們對技術特性的偏好在單獨考慮單個產品時與在比較中考慮兩個產品時是不同的。這反過來又幫助我們為IT設計提供重要的實用指南。其次，我們的工作通過展示IT產品評估和偏好如何在不同的環境中變化，為現有的技術采用文獻做出了貢獻。我們的研究對更廣泛的技術采用文獻的影響可能是深遠的，既為現有的理論觀點提供了重要的邊界條件，也為未來研究的設計提供了方法上的見解。

2.Literature Review and Hypotheses Development

During usability testing, evaluators assess various product features（ According to ISO/IEC 9126 (ISO 1991), a feature represents "a set of attributes … which bear on the effort needed for use and on the individual assessment of such use " (Bevan and Macleod 1994, p. 136).） to determine their perceived importance in a specific context. As discussed, the evaluation context can significantly influence the assessment of a technology and its various features. Carefully matching the evaluation criteria, and the relative weightings of such criteria, to the context is crucial for gaining an accurate assessment. Unfortunately, much of the prior relevant literature has failed to adjust the criteria and weightings in differing contexts, such as when evaluating a single technology in isolation versus when comparing multiple technologies. For example, Venkatesh and Ramesh (2006) examined various criteria in a desktop versus device evaluation context. In their study, multiple websites were presented to study participants, and it is not clear whether assessments would hold if only one website was evaluated. In other words, the results from one evaluation context (e.g., evaluating and comparing multiple technologies) may not transfer to other evaluation contexts (e.g., evaluating a single technology).

2.文獻回顧與假設發展

在可用性測試期間，評估人員評估各種產品特性(根據ISO/IEC 9126 (ISO 1991)，一個特性代表“一組屬性……取決于使用所需的工作量以及對此類使用的單獨評估”（Bevan和Macleod 1994，第136頁）以確定它們在特定環境下的重要性。如前所述，評價環境對技術及其各種特性的評價有顯著影響。仔細地將評價標準和這些標準的相對權重與環境相匹配，對于獲得準確的評價是至關重要的。然而，許多現有的相關文獻未能在不同的環境中調整標準和權重（例如在單獨評估單個技術時與在比較多個技術時）。例如，Venkatesh和Ramesh（2006）在臺式機與設備評估環境中檢查了各種標準。在他們的研究中，研究人員向參與者展示了多個網站，如果只評估一個網站，評估是否有效還不清楚。換句話說，來自一種評估環境（例如，評估和比較多種技術）的結果可能不會轉移到其他評估環境（例如，評估一種技術）。

Additionally, depending upon the context, some features are easier to evaluate than others. For instance, according to Hsee et al. (1999), a technology feature can be hard or easy to evaluate independently, which is referred to as its evaluability. Specifically, the evaluability of a feature is determined by a person’s ability to independently map a given value assessment of a feature onto an evaluation scale (Hsee et al. 1999). Thus, “hard-to evaluate” means that “the evaluator does not know how good a given value on the attribute is without comparison,” and “easy-to-evaluate” refers to conditions where “the evaluator knows how good the value is” without comparison (Hsee 1996, p. 249). Consequently, hard to-evaluate does not mean that individuals do not know the value of a feature but that individuals have “difficulty determining the desirability of its value in the given decision context” (Hsee et al. 1999, p. 580). Thus, people can ascertain the value of a hard-to-evaluate feature but are unable to determine its worth without comparison (Hsee and Zhang 2004).
此外，根據上下文，有些特性比其他特性更容易評估。例如，Hsee et al.(1999)認為，技術特征可以是難以評價的，也可以是容易評價的，這被稱為技術特征的可評價性。具體來說，一個特征的可評估性取決于個人將要素的給定價值評估獨立映射到評估量表上的能力（Hsee等，1999）。因此，“難以評估”意味著“在沒有比較的情況下評估者不知道特征上的給定值有多好”，而“易于評估”指的是“在沒有比較的情況下評估者知道值有多好”(參見1996，第249頁)。因此，難以評價并不意味著個體不知道特征的價值，而是個體“在給定的決策環境中難以確定其價值的可取性”(Hsee et al. 1999, p. 580)。因此，人們可以確定一個難以評估的特征的價值，但是沒有比較就無法確定其價值(Hsee和Zhang 2004)。

Hsee and colleagues (1996; 1999; 2013) further argue that how individuals assess a hard- versus an easy-to-evaluate feature is different, depending on the evaluation context. When assessing a single product (i.e., a separate evaluation (SE))— because a hard-to-evaluate feature without comparison is hard to assess – people are more likely to base their evaluation on an easy-to-evaluate feature (e.g., aesthetics). Alternatively, when comparing two products (i.e., a joint evaluation (JE)), people can compare both easy- and hard-to-evaluate features. An example of a JE evaluation from Venkatesh and Ramesh is where participants evaluated multiple websites. As such, because hard-to-evaluate features (e.g., screen resolution, processing clock speed, and storage capacity) become more salient when being compared, they have a greater influence on any product assessment (Hsee et al. 1999). Because of the difference in evaluation focus between JE and SE contexts, a person’s perceptions toward the same product can change due to the shift of the focal product feature used in making the assessment. Ultimately, such changes in focus can lead to preference reversals (PRs). The EH theoretical lens has been found to be robust to a wide variety of evaluation contexts, such as payoffs of dispute settlements, job offers, and servings of ice cream (e.g., Bazerman et al. 1999; GonzálezVallejoa and Moran 2001; Hsee and Rottenstreich 2004; Todorov et al. 2007; Wilson and Arvai 2006). As such, the EH can provide insights for designers when conducting a heuristic evaluation or other types of usability evaluations in different contexts. Specifically, assessment of a feature can change across evaluation contexts (SE versus JE), even if everything else remains the same.4
Hsee及其同事(1996年;1999;2013年)進一步認為，個體如何評估一個困難的和一個容易評估的特征是不同的，這取決于評估的環境。評估單一產品（即單獨的評估（SE））時-因為一個難以評估的特征如果不進行比較是很難評估的-人們更傾向于基于一個易于評估的特征(例如，審美)來進行評估。另外，在比較兩種產品（即聯合評估（JE））時，人們可以比較易于評估和難以評估的功能。Venkatesh和Ramesh對JE進行評估的一個例子是，參與者評估了多個網站。這樣一來，由于在比較時難以評估的功能（例如屏幕分辨率，處理時鐘速度和存儲容量）變得更加突出，因此它們對任何產品評估都具有更大的影響力（Hsee et al.1999）。由于JE和SE環境下評估重點的不同，一個人對同一產品的看法可能會因進行評估時使用的重點產品特性的改變而改變。最終，這種關注點的改變會導致偏好逆轉(PRs)。人們發現，EH理論的視角在各種各樣的評估環境中都是穩健的，比如解決爭端的報酬、工作機會和冰淇淋的分量(例如，Bazerman等人1999年;GonzalezVallejoa和Moran 2001;Hsee和Rottenstreich 2004;Todorov et al. 2007;Wilson和Arvai 2006)。這樣，當在不同環境中進行啟發式評估或其他類型的可用性評估時，EH可以為設計師提供見解。具體而言，即使其他條件保持不變，對特征的評估也會在評估環境（SE與JE）之間發生變化。

In sum, the EH proposes that individuals focus on different technology features in different contexts (i.e., when evaluating a single product in isolation versus when simultaneously evaluating two products). When evaluating a single product, individuals rely more on easy-to-evaluate features and perceive those features more important. In such a scenario, technology products with more favorable easy-to-evaluate features will more likely receive a higher evaluation. In contrast, when evaluating two products, individuals rely more on hard-to-evaluate, but easy-to-compare, features and perceive those features more important. In such a scenario, technology products with more favorable hard-to-evaluate features will likely receive a higher evaluation. Such changes in focus can lead to a PR. Thus, we propose
綜上所述，EH建議人們在不同的環境下關注不同的技術特性（即，單獨評估一個產品時與同時評估兩個產品時）。在評估單個產品時，個人更多地依賴于易于評估的特性，并且認為這些特性更重要。在這種情況下，具有更易于評估的特性的技術產品更有可能獲得更高的評價。相比之下，在評估兩種產品時，人們更多地依賴于難以評估但易于比較的特征，以及那些更重要的特征。在這種情況下，具有更佳難以評估特性的技術產品可能會得到更高的評價。焦點的這種變化可能導致PR。 因此，我們建議

H1: When simultaneously evaluating two IT products, the IT product with the more favorable hard-to-evaluate, but easy-to-compare feature, will be evaluated higher.
H2: When independently evaluating two IT products, the IT product with the more favorable easy-to-evaluate feature will be evaluated higher.
H1:在同時評價兩個IT產品時，有較難評價但易于比較的特征的IT產品評價較高。
H2:在獨立評價兩個IT產品時，有更容易評價特征的IT產品評價更高。

3.Methodology and Results

We first describe two exploratory pilot studies. We then present the two primary experiments that build on the pilot studies and directly test our hypotheses.

3.方法與結果

我們首先描述兩個探索性試點研究。 然后，我們介紹基于試點研究提出兩個主要實驗，并直接檢驗我們的假設。

3.1Exploratory Pilot Studies

Prior to conducting the main experiments, we ran two exploratory pilot studies to examine how people would perceive different technology features when evaluating Microsoft PowerPoint (PPT) versus Visio and the Apple iPad versus the Motorola Xoom (see Appendices A and B for the details). These pilot studies allowed us to refine our tasks, experimental procedures, and measures for the main studies, and are also reported for both completeness and for aiding future research. In both pilot studies, we found the EH to be partially supported. When both options were simultaneously compared, as expected, both PPT and the iPad were evaluated higher than Visio and Xoom, respectively; however, we did not see a product preference reversal.

3.1探索試點研究

在進行主要實驗之前，我們進行了兩個探索性的試點研究，以檢驗人們在評價Microsoft PowerPoint (PPT)與Visio、蘋果iPad與摩托羅拉Xoom時如何看待不同的技術特性(詳見附錄A和B)。這些試點性研究使我們能夠完善主要研究的任務，實驗程序和措施，并報告其完整性和對未來研究的幫助。在兩項試點研究中，我們發現EH均得到部分支持。 如預期的那樣，當同時比較這兩個選項時，PPT和iPad的評估分別高于Visio和Xoom。 但是，我們沒有看到產品偏好反轉。

In hindsight, a problem with utilizing “known” products (e.g., that have different brand awareness, market shares, and features) is that we could not control, or adequately account for, a subject’s prior relative knowledge or opinions of these commercial products. Additionally, because we highlighted real product features in these evaluations, whether a feature was easy- or hard-to-evaluate was assumed based on the guidance of the prior literature rather than being carefully manipulated. Thus, because participants were less familiar with Visio and Xoom, they were also less likely to fully understand the difficulty to evaluate features and/or simultaneously suffer from a bias toward the more popular products (Erdem and Swait 1998). These results suggest that it may be difficult to overcome differences in brand awareness without a more sophisticated research approach (e.g., anonymize the brand). To overcome the limitations of the pilot studies and following the guidance of the existing EH literature, we chose a “brandless” product category (i.e., wireless Internet service) where brand awareness could be controlled and the easy- and hard to-evaluate product features could be carefully manipulated.
事后看來，使用“已知”產品（例如具有不同的品牌知名度，市場份額和功能）的問題是，我們無法控制或充分考慮受試者對這些商業產品的先前相對知識或看法。另外，因為我們在這些評估中強調了真實的產品特性，所以一個特性是容易還是難以評估是基于先前文獻的指導而不是仔細操作的。因此，由于參與者不太熟悉Visio和Xoom，他們也不太可能完全理解評估功能的困難和/或同時對更受歡迎的產品有偏好(Erdem和Swait 1998)。這些結果表明，如果沒有更復雜的研究方法(例如，將品牌匿名化)，可能很難克服品牌知名度的差異。為了克服試點研究的局限性，在現有EH文獻的指導下，我們選擇了一種“無品牌”產品類別（即無線互聯網服務），在該類別中可以控制品牌知名度，并且產品特性的評估難易可以得到精心的處理。

3.2 Experiment 1

Task Context Development
While there are many product features that could influence a person’s choice making, the EH literature recommends that a hard-to-evaluate feature be “sufficiently important” so that the product with the superior performance on this attribute will be favored when making a product comparison assessment (i.e., a JE context) (González-Vallejo and Moran 2001). The hard to-evaluate feature should also be sufficiently difficult for most consumers to assess without comparison. For example, from the EH literature, hard-to-evaluate features have routinely been operationalized as numeric values related to a particular product feature (e.g., a screen resolution of 1920 × 1080 versus 1366 × 768; a product weight of 2.5 versus 1.2 kg). Likewise, when selecting an attribute when evaluating a product in isolation (i.e., a SE context), the feature should again be important and relatively easy to evaluate without comparison. Again, using guidance from the literature (Hsee 1996), easy-to-evaluate features are typically operationalized as dichotomous factors (e.g., exists versus doesn’t exist; low versus high).

3.2實驗1

任務環境開發
雖然有許多產品特性可能會影響一個人的選擇，但是EH文獻建議一個難以評估的特性是“足夠重要的”，這樣在進行產品比較評估時，在這個屬性上性能更好的產品將會受到青睞(例如，(Gonzalez-Vallejo和Moran 2001)。難以評估的特性對于大多數消費者來說，如果不進行比較，也很難進行評估。例如，在EH文獻中，難以評估的特性通常被操作化為與特定產品特性相關的數值(例如，屏幕分辨率為1920×1080，而不是1366×768;產品重量為2.5千克對1.2千克)。同樣，在單獨評估產品（即SE環境）時選擇屬性時，該特性應該同樣重要，并且無需比較即可輕松評估。再次，根據文獻(Hsee 1996)的指導，易于評估的特征通常被操作化為二分因素(例如，存在與不存在;低和高)。

Based on lessons learned from our pilot studies, Experiment 1 examined how participants evaluated different wireless Internet services. To understand how technology features influence product choice decisions within the context of wireless Internet services for our target population (i.e., what are the important features), we surveyed 33 undergraduate students from a college-wide, junior-level business class at a large public university in the northeast region of China. Students were asked to list at least two features which they thought were important for wireless Internet services (see Table 1 for a list of features and their frequency of occurrence). Based on the results of this survey and following the guidance of the extant literature, we chose connection speed as the hard-to-evaluate feature because this feature was an extremely important feature, it is almost always reported numerically, and would be hard to evaluate without comparison (e.g., 100 versus 50 mbps). Additionally, given the timeliness of cybercrime and its importance as well as the ability to represent this feature as a dichotomous variable, we chose secured connection as the easy-to evaluate feature (e.g., secured versus not secured connection).
根據我們從試點研究中獲得的經驗教訓，實驗1研究了參與者如何評估不同的無線互聯網服務。在無線互聯網服務范圍內，為了了解技術特征如何影響目標人群的產品選擇決策（即重要特征是什么），我們調查了中國東北地區一所大型公立大學的33名本科生，他們來自一個全學院的初級商務班。要求學生列出至少兩個他們認為對無線Internet服務很重要的特性(特性及其出現頻率的列表見表1)。根據調查結果，并根據現有文獻的指導，我們選擇連接速度作為難以評估的特性，因為該特性是非常重要的特性，幾乎總是以數字形式報告，并且很難評估無需比較（例如100與50 mbps）。此外，考慮到網絡犯罪的及時性及其重要性，以及將該特征表示為二分類變量的能力，我們選擇了安全連接作為易于評估的特征(例如，安全連接與不安全連接)。

Consider a context where two wireless Internet service options, Plan A and Plan B, are assessed. Here, Plan A is faster, but has no embedded security; Plan B is slower, but provides integrated security. When evaluating either Plan A or Plan B in isolation, individuals are more likely to perceive the security feature (easy-to-evaluate) more important. However, when evaluating both plans simultaneously, individuals are more likely to perceive the connection speed differences (hard-to-evaluate) more important. Thus, Plan A will be evaluated higher when jointly compared (H1); Plan B will be evaluated higher when evaluated separately (H2).
考慮一個環境，其中評估了兩個無線Internet服務選項，方案a和方案B。在這里，方案A更快，但沒有嵌入式安全;方案B比較慢，但是提供了集成的安全性。當單獨評估方案A或方案B時，個人更可能認為安全特性(易于評估)更重要。然而，當同時評估兩個計劃時，個體更可能認為連接速度差異(難以評估)更重要。因此，聯合比較時，方案A的評價會更高(H1);方案B單獨評估時的評估值更高(H2)。

Sample
The participants were from a college-wide, junior-level business class at a large public university in the northeast region of China; 69 students voluntarily participated in the study. Participants’ age ranged between 20 and 22, and their average age was 21.14 (SD .72); 59.15% were women. Each participant received about 1% of their final course grade for participating in the experiment.
樣本
參與者來自中國東北地區一所大型公立大學的一個全學院范圍的初級商務班;69名學生自愿參加了研究。參加者的年齡介乎20至22歲，平均年齡為21.14歲(SD .72);59.15%是女性。每個參與實驗的學生都得到了他們最終課程成績的1%。

Measures
The technology evaluation measure was developed by following the guidance from the extant literature (e.g., Dishaw and Strong 1999; Venkatesh et al. 2003); that is, “the degree to which a person has a favorable or unfavorable evaluation or appraisal” (Ajzen 1991, p. 188). Technology experience was collected to access participants’ self-reported background and experience with the focal technology (see Appendix C).
指標
技術評價指標是根據現有文獻（例如Dishaw和Strong，1999； Venkatesh等，2003）的指導制定的。就是說，“一個人對評價或評價的好壞程度”（Ajzen 1991，第188頁）。收集技術經驗以獲取參與者的自我報告背景和對焦點技術的經驗（請參閱附錄C）。

Task and Experimental Procedure
The task asked participants to imagine that their school planned to implement a new wireless Internet service and to evaluate either Plan A or Plan B or both (see Appendix D, Main Study 1). Participants were also asked to primarily focus on the plan’s connection speed and security features, with everything else (e.g., price) being equal.
After arriving at a computer classroom where the study was administered, participants were briefly introduced to the study and then directed to a secure website to finish the task and fill out a short background questionnaire. Following prior EA research (Hsee 1996; Hsee and Leclerc 1998), participants were randomly assigned to one of three groups (see Figure 1). Group 1 received and read Plan A and then completed the evaluation survey. Group 2 received and read Plan B and then completed the evaluation survey. Group 3 received and read both Plan A and Plan B and then completed the evaluation survey for both technologies.

任務與實驗程序
該任務要求參與者想象他們的學校計劃實施一項新的無線互聯網服務，并評估方案A或方案B或兩者進行評估（請參閱附錄D，主要研究1）。還要求他們主要集中在連接速度和安全特性,兩個方案的其他特性(如價格)是相同的。
到達負責研究的計算機教室后，向參與者簡要介紹了研究，然后將他們引導到安全的網站以完成任務并填寫簡短的背景調查表。根據先前的EA研究（Hsee 1996； Hsee和Leclerc 1998），參與者被隨機分配為三組（見圖1）。第一組接受并閱讀方案A，然后完成評估調查。第二組接受并閱讀方案B，完成評估調查。第三組分別接收并閱讀方案A和方案B，完成兩種技術的評估調查。

Manipulation Check
A manipulation check was used to assess whether Internet connection speed was a harder to evaluate feature than was security. In this check, participants in Groups 1 and 2 were asked (1) “Do you have any idea how fast Plan A/B is?” and (2) “Do you have any idea how secure Plan A/B is?” When answering, participants chose among five options, ranging from (1) = “I don’t have any idea.” To (5) = “I have a clear idea.” The mean evaluability score for speed (2.82) was significantly lower than that for security (3.50) (t (43) = -3.03; p < 0.01), confirming that security was perceived easier to evaluate than speed.
操作檢查
使用一個操作檢查來評估互聯網連接速度是否比安全性更難評估。在這項檢查中，第一組和第二組的參與者被問到(1）“您是否知道方案A / B有多快？” （2）“您是否知道方案A / B有多安全？” 回答時，參與者從5個選項中進行選擇，這些選項從(1)=“我不知道”到 (5) =“我有一個清晰的想法。” 速度的平均可評估性分數（2.82）顯著低于安全性的平均可評估性分數（3.50）（t（43）= -3.03； p <0.01），這證明安全性比速度更容易評估。

Analysis and Results
The Cronbach’s alpha of the technology evaluation measure was 0.94. A one-way ANOVA found no differences for gender, age, and wireless Internet experience across the three treatment groups. Two t-tests were conducted to compare the evaluation differences between Plan A and Plan B. First, a paired sample t-test was run using the data from Group 3; this analysis found the Plan A (with a faster connection speed) (Mean = 4.83; S.D. = 1.78) to be rated significantly higher than Plan B (Mean = 3.26; S.D. = 1.54) (t (23) = 2.47; p < 0.05; Cohen’s d = 0.94; a large effect). Thus, H1 was supported. Next, an independent sample t-test was run for Groups 1 and 2; this analysis found Plan A (Mean = 4.96; S.D. = 1.22) and Plan B (Mean = 5.82; S.D. = 0.97) to be significantly different (t (43) = -2.622; p # 0.05; Cohen’s d = 0.78; a medium effect), with improved security rated higher. Thus, H2 was also supported. Additionally, the results demonstrated a product PR across evaluation modes (see Table 2).
分析和結果
技術評價指標的克朗巴赫（Cronbach）alpha值為0.94。單因素方差分析發現，在三個實驗組中，性別、年齡和無線上網體驗沒有差異。進行了兩次t檢驗以比較方案A和方案B之間的評估差異。首先，使用來自第3組的數據進行配對樣本t檢驗。該分析發現方案A（連接速度更快）（平均值= 4.83; SD = 1.78）的評分明顯高于方案B（平均值= 3.26; SD = 1.54）（t（23）= 2.47; p <0.05 ；科恩（Cohen）d = 0.94；影響很大）。因此，支持H1。然后，對第1組和第2組進行獨立樣本t檢驗；該分析發現方案A（平均值= 4.96; SD = 1.22）和方案B（平均值= 5.82; SD = 0.97）有顯著差異（t（43）= -2.622; p＃0.05; Cohen d = 0.78;中等）效果），改進的安全性評分更高。因此，支持H2。此外，結果證明了跨評估模式的產品PR（請參見表2）。

Discussion
Experiment 1 supports the EH within the context of IT adoption, demonstrating that people’s perceptions of a feature’s importance are influenced by the evaluation contexts. However, Experiment 1 has some limitations. First, network security was framed as a dichotomous variable: Plan A having no security and Plan B having security. Therefore, it is possible that the evaluability of the security attribute was limited by its dichotomous nature. Second, the security feature’s evaluability was a characteristic of the feature per se and was not empirically manipulated. As discussed above, when making a joint (JE) versus separate (SE) evaluation, PRs occur because one feature is hard-to-evaluate and the other is easy-to-evaluate. Thus, to eliminate such concerns, if both connection speed and security features are hard-to evaluate, the relative importance of those two features should not change between the two evaluation contexts (i.e., JE versus SE) and a PR will not occur. To explore this rival hypothesis, we conducted a second experiment where security was operationalized as a continuous variable (i.e., security level 2 versus security level 5), thus empirically manipulating the security feature’s evaluability.
討論
實驗1在IT采用的背景下支持EH，表明人們對特性重要性的感知受到評價背景的影響。然而，實驗1有一些局限性。首先，將網絡安全性定義為一個二分變量:方案A沒有安全性，方案B有安全性。因此，安全屬性的可評估性可能受到其二分性的限制。其次，安全性的可評估性本身就是該特性的一個特征，沒有經驗地加以操縱。如上所述，在進行聯合(JE)和單獨(SE)評估時，發生PRs是因為一個特性難以評估，而另一個易于評估。因此，為了消除這些問題，如果連接速度和安全性都很難評估，則這兩個特性的相對重要性在兩個評估環境（即JE與SE）中不應該改變，并且不會出現PR。為了探究這個對立的假設，我們進行了第二個實驗，其中安全性被作為一個連續變量(即，安全級別2對安全級別5)，從而經驗地操作安全特性的可評估性。

3.3Experiment 2

Task Context
Like Experiment 1, participants assessed two different wireless Internet services where Plan A is faster but is less secure; Plan B is slower but is more secure (see Appendix D, Experiment 2). However, in this experiment, security was operationalized in two ways, with low and high evaluability. Using this modification, we had two evaluability conditions: hard/hard and hard/easy. In the hard/hard condition, both the connection speed and security features were hard-to-evaluate; specifically, participants were provided with a meaningless number for establishing the quality of the security feature. In the hard/easy condition, speed remained hard-to-evaluate, whereas security was relatively easy-to-evaluate (i.e., participants were told the meaning of the security rating number). Therefore, we predict that there will not be a joint-separate evaluation for the hard/hard condition and thus no PR will occur. However, for the hard/easy condition, a classic EH condition, a joint-separate evaluation will occur, and a PR will occur. As such, we propose that a PR will not occur in the hard/hard condition, but will occur in the hard/easy condition.

3.3實驗2

任務環境
與實驗1一樣，參與者評估了兩種不同的無線互聯網服務，其中方案A速度更快，但安全性更差;方案B較慢，但更安全(見附錄D，實驗2)。但在本實驗中，安全性以兩種方式實現，低可評估性和高可評估性。使用這個修改，我們有兩個評估條件:hard/hard（難/難）和hard/easy（難/易）。在hard/hard條件下，連接速度和安全特性都難以評估;具體來說，為確定安全特性的質量，向參與者提供了一個沒有意義的數字。在困難/容易的情況下，速度仍然難以評估，而安全性相對容易評估(即，參與者被告知安全評級數字的含義)。因此，我們預計不會對hard/hard條件進行聯合-單獨評估，因此不會發生PR。但是，對于hard/easy的情況，會發生經典的EH情況，聯合-單獨評估會發生，PR也會發生。因此，我們假設PR不會在hard/hard件下發生，而會在hard/easy狀態下發生。

Sample
The participants were from a college-wide, junior-level business class at the same university as Experiment 1; 82 students voluntarily participated in the study. Participants’ age ranged between 19 and 23, and their average age was 21.41 (SD .75); 59.76% were women. Each participant received about 1% of their final course grade for participating in the experiment.
樣本
參與者來自與實驗1所在大學相同的大學范圍內的初級商務班； 82名學生自愿參加了研究。 參與者的年齡介于19到23歲之間，平均年齡為21.41（SD .75）；59.76%是女性。每個參與實驗的學生都得到了他們最終課程成績的1%。

Task and Experimental Procedure
The measures were the same as Experiment 1. The tasks and procedures, however, were slightly different from Experiment 1 (see Figure 2). The participants were again divided into three groups, but the survey for each group contained two parts, which constituted three evaluation contexts by two evaluability conditions (i.e., six total conditions). Three evaluation contexts were the same as those for Experiment 1. The two evaluability conditions were hard/hard and hard/easy. In the hard/hard condition, both connection speed and security level were rated numerically and therefore both were hard to evaluate without comparison. In the hard/easy condition, connection speed remained hard to evaluate without comparison but security was made relatively easy to evaluate by telling participants the meaning of the numerical rating. Following Hsee (1996), the two evaluability conditions were designed within-subjects.
任務與實驗流程
指標與實驗1相同。但是，任務和過程與實驗1略有不同（請參見圖2）。 參與者再次分為三組，但每組的調查包含兩個部分，由兩個可評估條件（即六個總條件）構成三個評估環境。 三個評估環境與實驗1相同。這兩個評估條件分別為hard/hard和hard/easy。在hard/hard條件下，連接速度和安全級別都是用數字來評估的，因此不進行比較很難評估。在hard/easy條件下，如果不進行比較，連接速度仍然很難評估，但是通過告訴參與者數值評級的含義，安全性相對容易評估。根據Hsee（1996），這兩個可評估性條件是在受試者內部設計的。

Manipulation Check
A manipulation check was used to assess whether Internet connection speed was a harder to evaluate feature than security in the two evaluability conditions. In this check, participants in Groups 1 and 2 were asked (1) “Do you have any idea how fast Plan A/B is?” and (2) “Do you have any idea how secure Plan A/B is?” When answering, participants chose among five options, ranging from (1) = “I don’t have any idea” to (5) = “I have a clear idea.” In the hard/hard condition, the mean evaluability score for connection speed (2.40) was not significantly different from that for security (2.52) (t (54) = -0.73; p > 0.05), confirming that both features were deemed relatively hard to evaluate. In hard/easy condition, the mean evaluability score for connection speed (2.84) was significantly lower than that for security (3.33) (t (54) = -3.46; p < 0.05), confirming that security was perceived easier to evaluate than connection speed.
操作檢查
使用一個操作檢查來評估互聯網連接速度是否比安全性更難評估。在這項檢查中，第一組和第二組的參與者被問到(1）“您是否知道方案A / B有多快？” （2）“您是否知道方案A / B有多安全？” 回答時，參與者從5個選項中進行選擇，這些選項從(1)=“我不知道”到(5) =“我有一個清晰的想法。” 在hard/hard條件下，連接速度(2.40)與安全(2.52)的平均可評估得分沒有顯著差異(t (54) = -0.73;(p > 0.05)，證實這兩個特征都被認為是相對難以評估的。在hard/easy條件下，連接速度(2.84)的平均可評估得分顯著低于安全(3.33)(t (54) = -3.46;(p < 0.05)，確認安全性比連接速度更容易評估。

Analysis and Results
The Cronbach’s alpha of the technology evaluation measure was 0.97. No differences for gender, age, and wireless Internet experience were found across the three treatment groups. Two t-tests were used to compare the evaluation differences between Plan A and Plan B. In the hard/hard condition, a paired sample t-test was run using the data from Group 3; this analysis found Plan A (Mean = 5.91; S.D. = 1.07) to be rated significantly higher than Plan B (Mean = 2.85; S.D. = 0.69) (t (26) = 10.67; p < 0.05; Cohen’s d = 4.19; a large effect). Next, an independent sample t-test was run for Groups 1 and 2; this analysis found Plan A (Mean = 5.50; S.D. = 1.63) and Plan B (Mean = 5.72; S.D. = 1.44) to be equivalent (t (53) = -0.52; p > 0.05 Cohen’s d = 0.14). As proposed, a PR did not occur in the hard/hard condition (see Table 3).
Next, in the hard/easy condition, a paired sample t-test was run using the data from Group 3; this analysis found the Plan A (Mean = 4.94; S.D. = 1.55) to be rated significantly higher than Plan B (Mean = 3.56; S.D. = 1.48) (t (26) = 2.61; p < 0.05; Cohen’s d = 1.09; a large effect). Next, an independent sample t-test was run for Groups 1 and 2; this analysis found Plan A (Mean = 4.86; S.D. = 1.50) and Plan B (Mean = 5.75; S.D. = 1.01) to be significantly different (t (53) = -2.59; p < 0.05; Cohen’s d = 0.70; a medium effect), with improved security rated higher. Also, as proposed, a PR occurred in the hard/easy condition (see Table 3).
分析和結果
技術評價指標的克朗巴赫（Cronbach）alpha值為0.97。單因素方差分析發現，在三個實驗組中，性別、年齡和無線上網體驗沒有差異。進行了兩次t檢驗以比較方案A和方案B之間的評估差異。在hard/hard條件下，使用來自第3組的數據進行配對樣本t檢驗；該分析發現方案A（平均值= 5.91; SD = 1.07）的評分顯著高于方案B（平均值= 2.85; SD = 0.69）（t（26）= 10.67; p <0.05; Cohen d = 4.19;大影響）。接下來，對第1組和第2組運行獨立的樣本t檢驗；該分析發現，方案A（平均值= 5.50；標準差= 1.63）和方案B（平均值= 5.72；標準差= 1.44）是等效的（t（53）= -0.52； p> 0.05科恩d = 0.14）。按照提議，在hard/hard條件下不會發生PR（請參見表3）。
接下來，在hard/easy條件下，使用來自第3組的數據進行配對樣本t檢驗；該分析發現方案A（平均值= 4.94; SD = 1.55）的評分明顯高于方案B（平均值= 3.56; SD = 1.48）（t（26）= 2.61; p <0.05; Cohen d = 1.09; a效果大）。接下來，對第1組和第2組運行獨立的樣本t檢驗；該分析發現方案A（平均值= 4.86; SD = 1.50）和方案B（平均值= 5.75; SD = 1.01）有顯著差異（t（53）= -2.59; p <0.05; Cohen d = 0.70;中等）效果），改進的安全性評分更高。而且，如所提出的，PR在hard/easy狀態下發生（參見表3）。

4.Discussion

Based on the EH, when evaluating a single IT product, the easy-to-evaluate product feature was perceived more important. When two IT products were compared, the hard-to evaluate feature was perceived more important, resulting in a PR between the two evaluation contexts. Our two experiments showed that joint-separate evaluation PRs happen not only when one feature is dichotomous and the other is continuous, but also when both features are continuous. Also, Experiment 2 demonstrated that joint-separate evaluation PRs can be turned on and off by changing the evaluability of the features. Thus, as suggested by this theoretical lens, when comparing two IT products, individuals will more favorably evaluate the product with more desirable easy-to-compare features; when evaluating one IT product, individuals will more favorably evaluate the product with more desirable easy-to-evaluate features.

4.討論

基于EH，當評估單個IT產品時，容易評估的產品特性被認為更重要。當兩個IT產品進行比較時，難以評估的特征被認為更重要，從而導致兩個評估上下文之間的PR。我們的兩個實驗表明，聯合-單獨評價PRs不僅發生在一個特征是二分的，另一個特征是連續的情況下，而且發生在兩個特征都是連續的情況下。實驗2還表明，通過改變特征的可評價性，可以實現聯合-單獨評價PRs的開啟和關閉。因此，正如該理論觀點所建議的，當比較兩種IT產品時，個人會更傾向于評估具有更理想的易于比較的特性的產品。當評估一個IT產品時，個人會更傾向于評估具有更理想的易于評估的特性的產品。

5.Theoretical Contributions

This research makes two important theoretical contributions. First, these results contribute to HCI literature, suggesting that people’s perceived importance toward technology features can change in different evaluation contexts. Specifically, when only one IT product is evaluated, individuals are likely to rely more on easy-to-evaluate features. When there are at least two IT products being evaluated, individuals are more likely to rely more on hard-to-evaluate features. In other words, different product features are salient in different evaluation contexts. Thus, when examining the relative importance of features for a specific technology, researchers should be aware of the evaluation context and its potential influence on assessments. For example, Keil and Tiwana (2006) used conjoint analysis (a multi-attribute judgment analysis to derive the underlying structure of individuals’ decision rules) to explore the relative importance of various features within eight enterprise resource planning (ERP) systems. They found that participants rated system functionality higher than they rated ease of customization. From the EH perspective, ease of customization was relatively easy to assess because evaluators could rapidly identify whether the system could, or could not, be easily customized (i.e., a system was described as easy to customize or not). Alternatively, understanding which systems had all desired functionality was relatively harder to evaluate without comparison (i.e., which system [i.e., A through H], has the desired and/or better set of features?). Thus, the EH suggests that participants perceived those hard-to-evaluate but easy-to-compare criteria (e.g., system functionality) as more important than those easy-toevaluate features (e.g., ease of customization). Similarly, Venkatesh, Chan et al. (2012) found that usability is more important for service adoption than security provision. Here, the usability of e-government services could be judged based on the number of steps required by a consumer. Therefore, usability was hard-to-evaluate without comparison, playing a larger role when individuals have multiple e-government services in mind. To summarize, our study can help explain results from previous literature in terms of why certain technology features are perceived to be more important in certain contexts.

5.理論貢獻

本研究有兩個重要的理論貢獻。首先，這些結果對HCI文獻有貢獻，表明人們對技術特性的感知重要性可以在不同的評估環境中改變。具體來說，當只評估一個IT產品時，個人可能更依賴于易于評估的特性。當至少有兩個IT產品被評估時，個體更可能更多地依賴于難以評估的特性。換句話說，不同的產品特性在不同的評估環境中很重要。因此，在檢查特性對于特定技術的相對重要性時，研究人員應了解評估環境及其對評估的潛在影響。例如，Keil和Tiwana(2006)使用聯合分析(一種多屬性判斷分析，得出個人決策規則的底層結構)來探索八個企業資源規劃(ERP)系統中各種特征的相對重要性。他們發現，參與者對系統功能的評價要高于對自定義易用性的評價。從EH的角度來看，自定義易用性相對是容易評估的，因為評估人員可以快速確定系統是否可以輕易地進行定制（即，系統被描述為容易進行定制）。另外，如果不進行比較的話，理解哪些系統具有所有需要的功能相對比較困難（即哪個系統[即A至H]具有期望的和/或更好的特征集合？）。因此，EH表明參與者認為那些難以評估但易于比較的標準(例如，系統功能)比那些易于評估的特征(例如，易于定制)更重要。類似地，Venkatesh, Chan等人(2012)發現，對于服務采用來說，可用性比安全性更重要。在這里，電子政府服務的可用性可以根據用戶所需的步驟數量來判斷。因此，如果沒有比較，可用性很難評估，當個人考慮多個電子政府服務時，可用性扮演著更大的角色。總而言之，我們的研究可以幫助解釋先前文獻的結果，即為什么某些技術特性在某些上下文中被認為更重要。

Second, our study contributes to the technology adoption literature, suggesting that researchers need to be aware of the way in which technology evaluation is operationalized in future studies. Specifically, technology evaluation studies yield misleading results if participants are using a SE context, but the study assumes a JE context (i.e., if researchers are interested in the technology evaluation of a single technology, care must be taken to assure that participants are not considering other technologies). Our results show that the mechanisms that people follow when evaluating one IT product in isolation are fundamentally different from those when comparing two IT products. As such, the product features that influence technology evaluation when only one IT product is considered can be completely different from those driving evaluation and adoption when multiple IT products are being compared. For example, Wixom and Todd (2005) found accessibility to be important while timeliness was not in the context of evaluating a single data warehousing system. From the perspective of the EH, a possible explanation may be that accessibility is relatively easy-to-evaluate (i.e., accessibility relates closely with how easy the system is to use), while timeliness is relatively hard-to-evaluate (i.e., timeliness is hard to assess without comparison to another system). Therefore, accessibility is perceived more important than timeliness in such a context. To account for different evaluation processes, future research must take care to clearly understand and control the various adoption contexts5 in order to gain accurate usability assessments.
其次，我們的研究為技術采用文獻做出了貢獻，表明研究人員需要了解在未來的研究中技術評估的實施方式。具體地說，如果參與者使用的是SE環境，但該研究假設的是JE環境，技術評估研究就會產生誤導結果(即，如果研究人員對某一項技術的技術評估感興趣，必須注意確保參與者沒有考慮其他技術)。我們的結果表明，人們在單獨評估一個IT產品時所遵循的機制與在比較兩個IT產品時所遵循的機制是完全不同的。因此，當只考慮一個IT產品時，影響技術評估的產品特性可能與在比較多個IT產品時驅動評估和采用的產品特性完全不同。例如，Wixom和Todd(2005)發現可訪問性很重要，而及時性在評估單個數據倉庫系統時并不適用。從EH的角度來看，一種可能的解釋可能是可訪問性是相對容易評估的，（即，可訪問性與系統使用的容易程度密切相關），而及時性則相對難以評估（即及時性如果不與其他系統進行比較則很難評估）。因此，在這種情況下，可訪問性比及時性更為重要。為了說明不同的評估過程，未來的研究必須注意清楚地理解和控制各種采用環境（其他的環境因素，比如一個人對產品的主要使用，也可能會影響產品特性的相對價值以及對它們的評估方式。），以便獲得準確的可用性評估。

6.Practical Contributions

These results have three important practical implications. First, our work provides useful guidelines for designers when assessing usability. Depending upon whether a single or multiple products exist in a category, the relative importance of specific features may vary. As such, designers should be aware of how the salience of features may change depending upon the number of products in a particular category. Likewise, designers may need to adjust evaluation criteria and their relative weightings in different contexts to gain the most meaningful evaluations of features and products. For example, when designing a new technology product category (e.g., when Apple first released its iWatch), designers should focus more on easy-to-evaluate features to receive higher user evaluations. In contrast, in more mature technology product markets, designers should focus more on hard-to-evaluate features to receive higher evaluations from users.

6.實際貢獻

這些結果具有三個重要的實際意義。 首先，我們的工作為設計師評估可用性時提供了有用的指導。根據一個類別中存在單個產品還是多個產品，特定功能的相對重要性可能會有所不同。因此，設計師應該意識到特性的顯著性是如何隨著特定類別產品的數量而變化的。同樣，設計師可能需要調整評估標準及其在不同環境中的相對權重，以獲得對特性和產品最有意義的評估。例如，在設計一個新的技術產品類別時(例如，當蘋果首次發布iWatch時)，設計師應該更多地關注易于評估的功能，以獲得更高的用戶評價。相比之下，在更成熟的技術產品市場中，設計師應該更多地關注難以評估的功能，以獲得用戶更高的評價。

Second, consumers of IT products will benefit by becoming aware of the tendency to rely more heavily on hard-to-evaluate features when comparing multiple products. According to Hsee and Zhang (2004), people have better experiences with options with the more favorable easy-to-evaluate features. To limit evaluation bias, people may want to first evaluate a technology in isolation, then evaluate the product against others to see whether and how initial evaluations change. In other words, while consumers may have better usage experiences with technology products with the more favorable easy-to-evaluate features, they may ultimately choose technology products with the more favorable hard-to-evaluate features by comparing multiple products. Consumers need to be made aware of how the evaluation context shapes product evaluation perceptions.
其次，在比較多個產品時更加傾向于難以評估的功能，這將使IT產品的消費者受益。Hsee和Zhang(2004)認為，人們對更易于評估的選項有更好的體驗。為了限制評估偏差，人們可能想要首先單獨評估一項技術，然后將產品與其他產品進行比較，以了解初始評估是否以及如何發生變化。換句話說，當消費者對易于評價的特征較好的技術產品有較好的使用體驗時，他們可能會通過比較多個產品最終選擇較難于評價的特征較好的技術產品。消費者需要了解評價環境是如何塑造產品評價感知的。

Third, for companies launching new IT products, our findings have implications for their marketing campaigns. For example, when no similar products are available in the marketplace, companies should emphasize the easy-to-evaluate features because these features are most salient to assessment perceptions. However, when multiple similar products are available, companies should emphasize their strongest hard-to-evaluate features. For example, in 2015, Apple released two new products, the iWatch 1 and iPhone 6s. For the iWatch 1, wearables were an emerging market with few similar products for comparison. Thus, Apple likely benefitted by emphasizing its easy-to-evaluate features, such as aesthetics and style. In contrast, for the iPhone 6s, a relatively mature market, Apple benefitted most by emphasizing its hard-to-evaluate features, such as battery quality, processing performance, resolution, or app store. In fact, Apple followed this guidance in the official Apple advertising videos for the release of the iWatch 1 and iPhone 6s. For the iWatch 1, you will find scant information about its detailed capabilities. In contrast, for the iPhone 6s, advertising is packed with new technical features that are hard to evaluate without comparison.6 Apple seems to have embraced the EH in its marketing strategy.
第三，對于推出新IT產品的公司，我們的發現對他們的營銷活動有影響。例如，當市場上沒有類似的產品時，公司應該強調易于評估的特性，因為這些特性對于評估感知來說是最突出的。但是，當有多個類似的產品可用時，公司應該強調它們最強大的難以評估的特性。例如，2015年，蘋果發布了兩款新產品，iWatch 1和iPhone 6s。對于iWatch 1來說，可穿戴設備是一個新興市場，幾乎沒有類似產品可供比較。因此，蘋果可能通過強調美學和風格等易于評估的功能而獲益。相比之下，iPhone 6s是一個相對成熟的市場，蘋果受益最大的是強調其難以評估的功能，比如電池質量、處理性能、分辨率或應用商店。事實上，蘋果在發布iWatch 1和iPhone 6s的官方廣告視頻中就遵循了這一指導。對于iWatch 1，你會發現關于其詳細功能的信息很少。相比之下，對于iPhone 6s來說，廣告充滿了新技術特性，如果不進行比較，很難對其進行評估。蘋果似乎已經接受了EH的營銷策略。

7.Limitations and Opportunities for Future Studies

While making a significant contribution to our understanding of technology choice, our work has some limitations. Although broadly applied (e.g., Bazerman et al. 1999; González-Vallejoa and Moran 2001; Hsee and Rottenstreich 2004; Todorov et al. 2007; Wilson and Arvai 2006), the EH has several characteristics which can limit its application. First, the theory deals with the comparison of two products; clearly, consumers often face more than two product options (McCracken 2010). Nevertheless, our results help to build a foundation for future studies investigating more than two options. Second, the theory focuses on two products that have a trade-off between easy- and hard-to-evaluate features. Future studies can focus on various mixes of easy- and hard-to-evaluate features. Third, the theory assumes that individuals have reasonable information on the products being evaluated so that they can objectively evaluate each option. When having limited information, individuals may make their decisions based on other factors, such as the visual appeal, brand, and even extrinsic factors such as shopping atmospherics (Kotler 1973) and website quality (Wells et al. 2011).7 Future studies can focus on these interesting scenarios. Another limitation relates to the experimental methodology with primarily student participants. Given our objective for clear-cut theory testing, we carefully controlled the manipulation of the technology features in order to maximize measurement precision, limiting generalizability and realism. However, by using three different product categories and a relatively diverse set of participants across the pilot studies and main experiments, the results were consistent across these varying conditions. Nevertheless, the design of our experiments was artificial; thus, the results may be limited to the specific IT products, tasks utilized, and subject populations in these studies. Clearly, these limitations must be considered when interpreting our results. Future studies can explore other IT products and associated features with more diverse samples (e.g., samples drawn with Amazon Mechanical Turk) to examine the robustness of various contingencies and contexts.

7.局限性和未來研究方向

在為我們對技術選擇的理解做出重大貢獻的同時，我們的工作也有一些局限性。盡管EH已得到廣泛應用（例如Bazerman等，1999;González-Vallejoa和Moran 2001; Hsee和Rottenstreich 2004; Todorov等，2007; Wilson和Arvai 2006），但EH具有一些可能會限制其應用的特征。首先，該理論涉及兩個產品的比較;顯然，消費者經常面臨兩種以上的產品選擇(McCracken 2010)。盡管如此，我們的研究結果有助于為未來研究更多的選擇奠定基礎。其次，該理論側重于在易于評估和難以評估的功能之間進行權衡的兩種產品。未來的研究可能集中在易于評估和難以評估的功能的各種組合上。第三，該理論假設個人對被評估的產品有合理的信息，因此他們可以客觀地評估每個選項。當信息有限時，個人可能會根據其他因素做出決定，如視覺吸引力、品牌，甚至外部因素，如購物氛圍(Kotler 1973)和網站質量(Wells et al. 2011)。未來的研究可以專注于這些有趣的場景。另一個限制涉及主要是學生參加的實驗方法。鑒于我們的目標是進行清晰的理論測試，我們仔細控制了技術功能的操縱，以最大程度地提高測量精度，從而限制了通用性和真實性。但是，通過在試點研究和主要實驗中使用三種不同的產品類別和一組相對不同的參與者，結果在這些變化的條件下是一致的。然而，我們的實驗設計是人為的。因此，結果可能僅限于這些研究中的特定IT產品，所使用的任務和主題人群。顯然，在解釋我們的結果時必須考慮這些限制。未來的研究可以探索其他IT產品和與更多樣化的樣本(例如，使用Amazon Mechanical Turk繪制的樣本)相關的特性，以檢查各種意外情況和環境的穩健性。

In Experiment 2, we explored nuances of how to operationalize easy- and hard-to-evaluate product features within the bounds of the EH. Specifically, we demonstrated that joint-separate evaluation PRs can be turned on and off and that hard-to-evaluate features can be switched into easy-to-evaluate features by providing more information about the feature. Of course, it is likely that not all hard-to-evaluate features can be manipulated in this manner. For example, in the marketing literature, Nelson (1974) proposes that product features can be divided into search and experience features. Search features include a product’s color, size, the number of calories or ingredients, and can be obtained through second hand sources such as advertisement and word of mouth. Alternatively, experience features, typically obtained via exposure to the product, include a product’s design quality, aesthetics, fit, taste, or ease of use. Therefore, search features tend to be more objective and diagnostic, whereas experience features tend to be more subjective, characterized by uncertainty and equivocality (Hoch and Deighton 1989). Thus, it may be possible to convert hard-to-evaluate search features into easy-to-evaluate search features by providing more descriptive or comparative information. However, it may be challenging to transform hard-to-evaluate experience features into easy-to-evaluate features by simply providing more feature-related details. Clearly, additional research is needed to explore how technology features can be transformed into easy-to-evaluate features. It may be possible that different types of HCI environments (i.e., virtual product experiences) can be used to improve the evaluability of many experiential product features.
在實驗2中，我們探討了如何在EH范圍內操作容易和難以評估的產品特性的細微差別。具體而言，我們證明了可以打開和關閉聯合-單獨的評估PR，并且通過提供有關特征的更多信息來可以將難以評估的特征轉換為易于評估的特征。例如，在市場營銷文獻中，尼爾森（Nelson）（1974）提出可以將產品功能分為搜索特性和體驗特性。搜索特性包括產品的顏色，大小，卡路里或成分的數量，并且可以通過二手來源（例如廣告和口碑）獲得。另外，體驗特性（通常通過接觸產品獲得）包括產品的設計質量，美學，合身性，品味或易用性。因此，搜索特性趨向于更客觀和更具診斷性，而體驗特征趨向于更加主觀，以不確定性和模棱兩可為特性（Hoch and Deighton 1989）。因此，通過提供更多描述性或比較性信息，可以將難以評估的搜索特性轉換為易于評估的搜索特性。但是，僅通過提供更多與特性相關的詳細信息，將難于評估的體驗特性轉換為易于評估的特性可能是一項挑戰。顯然，還需要進行其他研究來探索如何將技術特性轉換為易于評估的功能。可能可以使用不同類型的HCI環境（即虛擬產品體驗）來提高許多體驗產品特性的可評估性。

8.Conclusion

Consumers are facing an ever increasing number of technology product choices. Organizations want to design better technology products to best meet the needs of current and future customers. The EH provides a useful theoretical lens for improving our understanding of people’s perceived importance toward different features and overall technology product evaluations. The results from two experiments showed that individuals indeed perceived different technology features to have different levels of importance and perceived the same technology differently in different evaluation contexts (i.e., JE versus SE). These results help to explain how designers can develop technology products with higher usability, why individuals sometimes choose the wrong technology, and how organizations can best position their products in differing market contexts.

8.結論

消費者面臨著越來越多的科技產品選擇。組織想要設計更好的技術產品來最好地滿足當前和未來客戶的需求。EH提供了一個有用的理論視角來提高我們對人們感知到的對不同特性和整體技術產品評估的重要性的理解。兩個實驗的結果表明，在不同的評價情境中，個體確實感知到不同的技術特征具有不同的重要性，對同一技術的感知也存在差異(即JE對SE)。這些結果有助于解釋設計師如何開發可用性更高的技術產品，為什么個人有時會選擇錯誤的技術，以及組織如何在不同的市場環境中最好地定位他們的產品。

總結

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