群眾外包翻譯計畫的志工滿意度研究：以TED開放翻譯計畫為例

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(1)A Thesis Presented to the Graduate Institute of Translation and Interpretation, National Taiwan Normal University 國立臺灣師範大學翻譯研究所碩士論文. Volunteer Satisfaction for Crowdsourcing Translation Projects: A Case Study of the TED Open Translation Project 群眾外包翻譯計畫的志工滿意度研究：以TED開放翻譯計畫為例. Thesis Advisor: Dr. Tze-wei Chen 指導老師：陳子瑋博士. Advisee: Ying-Chun Chen 研究生：陳映均. July 2013 中華民國一Ｏ二年七月.

(2) Acknowledgement. This thesis could not have been completed without the generous help I have received along the way. To my thesis advisor, Dr. Tze-wei Chen, thank you for your untiring support and guidance throughout this journey. It was both an honor and a pleasure to have the opportunity to learn from you in the field of interpretation practice and translation studies. To the chair of my supervisory committee, Dr. Chi-ya Chang, thank you for your invaluable improvement suggestions and for cheering me on. To my committee member, Dr. Lidia Cámara de la Fuente, thank you for going out of your way and offering so much input as a linguist and as a TED volunteer. To the commentator of my thesis proposal, Dr. Posen Liao, thank you for your advice on methodology that had helped tremendously in my research design. To the TED Translators who have participated in my survey, thank you for your valuable insights and kind words of encouragement. Special thanks to Krystian, Geoff, Ivan, Khalid, Unnawut, Sami, Elise, Chris, Hanna, Caroline, Anna, David and Namik for taking the time to share with me your TED stories and even following up with new thoughts and ideas. You have made this an amazing experience for me, as I enjoyed each and every conversation I had with you. To my dear friends at the GITI family, thank you for being such great role models and for the wonderful friendship. I would like to give a shout-out to Marcie for accompanying me through the whole process—from topic brainstorming to answering nitty-gritty questions about thesis writing, and to Bob for offering much-needed help on the day of the oral defense. To my lovely colleagues, thank you for patiently answering my questions about research analysis and backing me up at work while I was struggling to juggle. To my beloved family, thank you for your selfless love that I will always be indebted to. Finally, to the great inventors of technologies, thank you for making this world a smaller and more connected place..

(3) Abstract. Crowdsourcing has emerged in recent year as a new form of volunteering activity. The distributed nature of online volunteers enabled organizations to mobilize talents from around the world, but in the meantime, generated concerns over how to manage volunteer satisfaction and ensure project sustainability. This research uses the TED Open Translation Project as an example, and sets out to identify key volunteer requirements for a successful online volunteer project through quantitative survey and in-depth interviews. Using the Kano’s model of satisfaction, attributes along five dimensions—Communication Quality, Organization Support, Infrastructure, Work Assignment and Group Integration are investigated. Analysis shows that two attributes (One-dimensional factors) may impact both satisfaction and dissatisfaction. Seven factors (Must-have factors) may lead to dissatisfaction if not provided, and five factors (Attractive factors) can enhance volunteer satisfaction when provided. Specifically, allowing volunteers to see the impact of their contribution can create the highest satisfaction, and failing to provide a user-friendly translation platform will potentially bring the greatest dissatisfaction. In addition, volunteer translators who act as Language Coordinators in their local TED communities and volunteers with translation training backgrounds have slightly different expectations for the volunteering project. Overall, the 134 volunteers who participated in this research are satisfied with their experience with the TED Open Translation Project, especially with its interesting content and learning opportunities. Keyword: Crowdsourcing; the Kano’s model of satisfaction; TED Open Translation Project. i.

(4) 摘要. 近年來，群眾外包興起，成為新的志工投入形態。由於線上志工分佈各地，組織得以號召更廣泛的志工群，但也因此面臨志工滿意度與志工留任的管理議題。本研究以TED開放翻譯計畫為例，透過問卷與深度訪談了解志工對於線上開放翻譯計畫的期待與滿意要素。利用Kano二維滿意度模型，本研究將滿意要素依五大面向，包括溝通品質、組織支持、基礎建設、工作內容與團體融合度，研究其對滿意度的影響。分析結果得出兩項一維滿意度要素，對滿意度與不滿意度皆有影響；七項當然要素，若未具備將使得滿意度下降；以及五項能夠提升志工滿意度的魅力要素。其中，線上開放翻譯計畫若能夠讓志工看見其貢獻的價值，最能夠大幅提升志工滿意度，而若未能建置容易操作的翻譯平台，則對滿意度有最負面的影響。此外，負責管理各語言社群的志工和受過翻譯訓練的志工對線上開放翻譯計畫的期待與一般志工有些許不同。整體而言，本研究的 134位翻譯志工對TED開放翻譯計畫滿意度偏高，尤其滿意翻譯內容和學習新知識的機會。. 關鍵字：群眾外包、Kano滿意度模型、TED開放翻譯計畫. ii.

(5) Table of Content Abstract .................................................................................................................................... i Table of Content ...................................................................................................................... iii List of Tables ........................................................................................................................... v List of Figures .......................................................................................................................... vi Chapter 1. Introduction 1.1 Research background ......................................................................................................... 1 1.2 Research questions ............................................................................................................. 2 1.3 Relevance ........................................................................................................................... 2 Chapter 2. Conceptual framework 2.1 Crowdsourcing ................................................................................................................... 4 2.1.1 Definitions........................................................................................................... 4 2.1.2 Key success factors of crowdsourcing projects .................................................. 7 2.1.3 Motivation of the contributing crowd ................................................................. 8 2.1.4 Crowdsourcing translation .................................................................................. 9 2.1.5 TED Open Translation Project............................................................................ 11 2.2 Volunteer and work satisfaction ........................................................................................ 12 2.2.1 Satisfaction in the paid work setting ................................................................... 12 2.2.2 Job satisfaction theories ...................................................................................... 14 2.2.3 Antecedents and consequences of job satisfaction ............................................. 15 2.2.4 Measures of job satisfaction................................................................................ 18 2.2.5 Application of the Kano Model .......................................................................... 18 2.3 Volunteer motivation and satisfaction .............................................................................. 21 2.3.1 Measures of volunteer satisfaction....................................................................... 23 2.4 Chapter summary ............................................................................................................... 24 Chapter 3. Methodology 3.1 Research design ................................................................................................................. 25 3.2 Instrumentation .................................................................................................................. 26 3.2.1 Expert interviews ............................................................................................... 26 3.2.2 Online questionnaire ........................................................................................... 27 3.2.2.1 Background questions ......................................................................... 27 3.2.2.2 Satisfaction measurement instrument design ....................................... 28 3.2.2.3 Kano’s two-dimensional questions ...................................................... 30. iii.

(6) 3.2.2.4 TED OTP Satisfaction questions ......................................................... 32 3.2.2.5 Pilot study ............................................................................................ 32 3.2.2.6 Data collection ..................................................................................... 33 3.2.3 Qualitative interviews ......................................................................................... 33 3.3 Data analysis ...................................................................................................................... 34 3.3.1 Survey reliability and validity............................................................................. 34 3.3.1.1 Content validity................................................................................... 34 3.3.1.2 Construct validity ................................................................................ 34 3.3.1.3 Internal-consistency reliability............................................................ 35 3.3.2 Research questions analysis ............................................................................... 36 Chapter 4. Results and Discussion 4.1 Volunteer demographics and background ......................................................................... 38 4.1.1 Translation related experience ............................................................................ 39 4.1.2 Volunteer involvement and contribution ............................................................ 40 4.1.3 Volunteer motivation .......................................................................................... 41 4.2 Kano categorization of volunteer satisfaction factors ........................................................ 44 4.2.1 Volunteer satisfaction coefficients ...................................................................... 46 4.3 Effect of background variables .......................................................................................... 48 4.3.1 Language Coordinator role as a variable ............................................................ 48 4.3.2 Translation training as a variable ........................................................................ 50 4.3.3 Volunteer contribution as a variable ................................................................... 51 4.4 Volunteer satisfaction with TED OTP ............................................................................... 52 4.5 Interview results and discussion ........................................................................................ 54 4.5.1 Organization support and infrastructure ............................................................. 55 4.5.2 Communication quality....................................................................................... 57 4.5.3 Work assignment ................................................................................................ 59 4.5.4 Group integration ................................................................................................ 62 4.5.5 Overall satisfaction, intention to stay and advocacy ........................................... 64 Chapter 5. Conclusion 5.1 Managerial Implications .................................................................................................... 67 5.2 Limitations and suggestions for future studies .................................................................. 70 Reference ................................................................................................................................ 72 Appendix I: Online survey questionnaire .............................................................................. 79. iv.

(7) List of Tables Table 3.1 Initial list of volunteer satisfaction factors .............................................................. 29 Table 3.2 Kano evaluation table .............................................................................................. 31 Table 3.3 Survey reliability...................................................................................................... 35 Table 3.4 Volunteer satisfaction factor loadings ..................................................................... 37 Table 4.1 Interviewee profile ................................................................................................... 38 Table 4.2 Volunteer satisfaction factors categorization ........................................................... 46 Table 4.3 Volunteer satisfaction coefficients ........................................................................... 47 Table 4.4 Kano categorization of Language Coordinators and non-Language Coordinators ............................................................................................................................. 50 Table 4.5 Kano categorization of volunteers with and without translation training ................ 51 Table 4.6 Kano categorization of volunteers with high and low contribution......................... 52 Table 4.7 TED OTP satisfaction survey results ....................................................................... 53. v.

(8) List of Figures Figure 2.1 Critical Success Factors Model of Crowdsourcing ................................................ 8 Figure 2.2 Job Characteristics Model ...................................................................................... 16 Figure 2.3 Antecedents of Job Satisfaction ............................................................................. 17 Figure 2.4 The Kano’s model of customer satisfaction ........................................................... 19 Figure 4.1 Working languages of survey respondents ............................................................ 39 Figure 4.2 Translation training background of survey respondents ........................................ 40 Figure 4.3 Top volunteer motivations of survey respondents ................................................. 42 Figure 4.4 Preference profile of TED translators .................................................................... 48 Figure 4.5 Volunteer satisfaction with TED OTP ................................................................... 54. vi.

(9) Chapter 1. Introduction 1.1 Research background Crowdsourcing is the business model of soliciting ideas or production solutions through an open call to the crowd (Brabham, 2008; Howe, 2006). In practice, a consumer goods company may post an R&D problem online and offer rewards to the best solutions proposed, and a social network website can develop a collaborative translation platform for its users to help localize its service into different languages (Howe, 2008). Thanks to technological advances, more and more organizations, particularly new, web-based platforms, are tapping into the productive power of the crowd for tasks previously undertaken by employees (ibid). While some organizations offer financial rewards, in many cases the works are voluntary. In other words, crowdsourcing is not only changing the way content is produced; it has created new channels of volunteering for those wishing to contribute their knowledge and skills.. For organizations that rely heavily on volunteer work, volunteer recruitment and retention strategies are key to their future sustainability (Martinez & McMullin, 2004). Literature on volunteerism mainly centers around direct service volunteers, with a focus on what motivates them (e.g. Clary et al., 1998; Cnaan & Goldberg-Glen, 1991). While the understanding of volunteer motivation can provide guidance for better recruiting, relatively few researches touch on volunteer satisfaction, which is found to be predicators of volunteers’ intent to stay (Galindo-Kuhn & Guzley, 2001). Similarly, researches on online collaboration activities that emerged in the past five years continue to explore the drivers behind volunteer participation (e.g. Borst, 2010; Hertel, Neidner & Hermann, 2003; Lakhani & Wolf, 2007).. This research uses the TED Open Translation Project (OTP) as an example and sets out to investigate volunteer expectations and experience based on the five dimensions established in Galindo-Kuhn & Guzley’s (2001) Volunteer Satisfaction Index (VSI). Drawing on literature on online volunteering activities, the questions are modified to better fit the crowdsourcing context. Furthermore, this study explores the relative importance of each satisfaction factor using the Kano’s Model of satisfaction to measure volunteers’ satisfaction as well as dissatisfaction with the presence and absence of specific functionalities and categorizes the factors into four groups: “Must-. 1.

(10) have”, “One-dimensional”, “Attractive” and “Indifferent” (Kano, Seraku & Tsuji, 1984; Matzler & Hinterhuber, 1998). The questionnaire is then applied on TED volunteer translators to gauge their level of satisfaction with the project, particularly regarding its performance around “One-dimensional,” “Must-have” and “Attractive” factors. As an exploratory research, this study also looks at the potential effect of volunteers’ background variables on their expectations for different satisfaction factors. With over 9,000 translators contributing to subtitling TED talks in 102 languages as of June 2013, the TED OTP is used here as a case example for online translation crowdsourcing project in the non-profit area, where no financial incentives are given. 1.2 Research question Volunteer satisfaction is the premise for loyalty (Wisner, Stringfellow, Youngdahl & Parker, 2004), and satisfaction derives from fulfilling or exceeding expectations (Locke, 1976). However, the two-dimensional nature of satisfaction factors suggests that the relationship between fulfillment and satisfaction is not always linear (Matzler & Hinterhuber, 1998). Therefore, the main purpose of this study is to identify the basic functional requirements expected of an online crowdsourcing translation projects. The understanding of volunteer expectation can facilitate future design of similar projects, especially for nonprofit organizations that wish to ensure resources are pulled into the most effective areas. By focusing on volunteer satisfaction, this research seeks to answer the following questions: 1. What are TED Translators’ views on the key satisfaction factors for an online volunteer translation project? 2. How well does the TED Open Translation Project perform along different satisfaction factors? 3. Does different background variables contribute to differences in volunteers’ perceived importance of key satisfaction factors? 1.3 Relevance For knowledge-thirsty web users around the world, there are now ample opportunities to acquire educational resources previously unavailable to them. Massive open online course (MOOC) projects such as Coursera and Khan Academy are changing the face. 2.

(11) of education by offering free courses from top-tier universities. On Coursera, for example, a single course on Introduction to Finance had over 100,000 students enrolled. Language barriers, however, threaten to undermine learning effectiveness for non-English speakers, creating a need for translated lecture videos. The success of online crowdsourcing projects hinges upon the careful design of tasks and incentives tailored to attract the most effective participants (Lohr, 2009). As TED is a platform that offers equally educational resources in the form of lecture-like speeches, the results of this paper can hopefully shed lights on how organizations can engage volunteers for content translation efforts.. 3.

(12) Chapter 2. Literature review 2.1 Crowdsourcing Web users contribute all sorts of valuable resources online every day, sometimes without them knowing it. YouTube, for example, functions fully on user-generated content for its service, and every time people type the letters of character recognition CAPTCHAs to pass website security systems, they are facilitating the digitalization of books and newspaper archives (von Ahn, Maurer, McMillen, Abraham & Blum, 2008). Based on existing examples, online contributions can fall into two simple classifications: Active contributions consist of the intentional sharing of opinions and ratings, software codes, expertise or goods and services; passive contributions refer to passively sharing information and resources such as purchasing behavioral data that helped Amazon better make product recommendations, web-linking behaviors that form the basis of Google Search’s algorithm and idle computing capacity leveraged by Skpye for its VoIP services (Cook, 2008). Many companies were quick to tap into the potential of online user contributions by establishing a system that can aggregate these external resources for product improvement, cost reduction and a diversity of purposes (ibid). Such system, as Wikipedia demonstrates, can be an open platform that encourages volunteers to work toward a common goal (“building a free, accurate, global encyclopedia”) while having a volunteer-based maintenance taskforce in place for quality control1. This present study focuses mainly on voluntary contributions made online through “crowdsourcing”—the new buzzword that denotes the emerging activity of outsourcing to the crowd (Howe, 2006). 2.1.1 Definitions The term “crowdsourcing” came into public awareness following Jeff Howe’s (2006) publication of his Wired Magazine article. Drawing from the rise of non-professional photographers in the stock photography industry, he defined the phenomenon as “the act of taking a job traditionally performed by employees and outsourcing it to an undefined, generally large group of people in the form of an open call” (ibid). Brabham (2008) later described it as an “online, distributed problem-solving and production model”.. 1. http://en.wikipedia.org/wiki/Wikipedia:Maintenance. 4.

(13) In its broadest sense, crowdsourcing can be applied to all activities that leverage the contribution of a large, distributed group of people. It is often used interchangeably with “open innovation” and “collective intelligence”, and can include Open Source Initiatives, in which software codes are shared for program development and refinement (Borst, 2010). Crowdsourcing is in fact not a new concept. Many organizations have benefited from the contributions of the general public for activities such as content creation, idea generation and solution submission. The consumer goods company, Procter & Gamble, for example, posted its research and development questions on open innovation websites, offered a reward for the best solution and kept the intellectual property (Howe, 2008, p.9-10). The popularity of this idea in recent years is driven partly by the greater complexity of the business environment and organizations’ need to look for external expertise (Chesbrough, 2003), and partly by the wider accessibility of tools and technology that even amateurs can master (Howe, 2008). The growing interest in crowdsourcing has also led to an accumulating amount of studies trying to make sense of it (Bayus, 2012; Lakhani & Wolf, 2005; von Krogh & von Hippel, 2006). After reviewing varying definitions and characteristics of crowdsourcing, Estellés-Arolas and González-Ladrón-de-Guevara (2012) attempted to present an exhaustive description of this activity: Crowdsourcing is a type of participative online activity in which an individual, an institution, a non-profit organization, or company proposes to a group of individuals of varying knowledge, heterogeneity, and number, via a flexible open call, the voluntary undertaking of a task. The undertaking of the task, of variable complexity and modularity, and in which the crowd should participate bringing their work, money, knowledge and/or experience, always entails mutual benefit. The user will receive the satisfaction of a given type of need, be it economic, social recognition, self-esteem, or the development of individual skills, while the crowdsourcer will obtain and utilize to their advantage that what the user has brought to the venture, whose form will depend on the type of activity undertaken. The definition covers the three key elements of crowdsourcing activities: the crowd, the initiator and the process, with an emphasis on the benefits for both the crowd and the initiating organization. The crowd refers to participants of crowdsourcing projects. They are not employees. 5.

(14) or workers along a company’s value chain; rather, they are a large group of “distributed, plural, collaborative” individuals (Brabham, 2008). The so-called “crowd” is usually regarded as non-experts or amateurs, but previous surveys showed that its composition often include people with professional credentials (EstellésArolas & González-Ladrón-de-Guevara, 2012). They can participate in crowdsourcing projects as an individual, but in many cases they collaborate with each other. Franke & Sonali (2003) for example observed that a lot of product innovation happens within voluntarily assembled communities of end-users. As contributors are not constrained by contractual obligations, they choose whether or not to offer their support at free will, driven either by intrinsic or extrinsic needs (Lakhani & Wolf, 2005).. The initiator is an organization or an individual who puts up a task and asks for the crowd’s voluntary support. It can be for-profit or not-for-profit by nature, but it is often assumed that the key benefit of using online voluntary resources is cost reduction, since contributors generally receive small or no financial rewards (Borst, 2010). However, as the experience of Facebook and Cisco shows, hosting crowdsourcing projects may require considerable resources, sometimes more than business as usual (Hosaka, 2008; Jouret, 2009). Yet with the help of volunteers, initiators enjoy the many advantages of having external talents and knowledge, such as increased efficiency, improved product quality and a more engaged and satisfied customer base (Borst, 2010; Howe, 2008).. The process of crowdsourcing can be seen as a model of problem solving, production, open innovation, business strategy, customer engagement or labor management, depending on the underlying purpose of the organizing firm. Despite the differences in how each organization orchestrates such activities, the Internet is almost present in all crowdsourcing processes. As Malone, Laubacher & Dellarocas (2010) pointed out, wider accessibility of tools and communication technologies has enabled communities to connect and collaborate, creating a virtual world of collective intelligence. The distributed nature of the Internet also allows crowdsourcing projects to scale up easily, without necessitating a broad and deep contribution (Cook, 2008). For instance, only about one in every 1,000 Wikipedia users contributes to the creation of its content, and active contributors only have to complete small tasks each time (ibid). 6.

(15) Crowdsourcing is capitalizing on the ability of the network to “divvy up an overwhelming task—such as the writing of an exhaustive encyclopedia—into small enough chunks that completing it becomes not only feasible, but fun” (Howe, 2008, p.11). 2.1.2 Key success factors of crowdsourcing projects Though the benefits of crowdsourcing seem appealing, organizations wishing to take advantage of the collective wisdom need to make an equally compelling case to attract public participation.. Malone et al. (2010) collected around 250 cases of crowdsourcing applications across a diverse range of areas and identified the “genes,” or building blocks of collective intelligence. The authors suggest that all organizations trying to initiate crowdsourcing projects answer the following four fundamental questions: . What is being done? The organization should decide if they wish to engage the crowd to create something new, or to make a decision. For example, they can ask the crowd to produce new videos, or to vote on the best videos.. . Who is doing it? The organization should consider if the crowd, instead of traditional management, might have the abilities required to perform the tasks more efficiently and effectively.. . Why are they doing it? The organization should make the strategic decision whether to appeal to money, love or glory to motivate the crowd.. . How is it being done? Once the organization decides to engage the crowd for content creation, they should also evaluate if the activities at hand can be divided into smaller tasks and worked on in a distributed manner. If not, they need to have a mechanism in place to manage the interdependencies of collaborated work. On the other hand, if the crowd is called upon for decision-making, the organization will have to determine whether group decision or individual decisions are required.. After the design decisions are made, the organization can pull together the appropriate elements to develop their own initiatives. In a similar attempt to conceptualize the phenomenon, Sharma’s (2010) study drew on outsourcing literature as well as case examples to propose a success model for crowdsourcing (Figure 2.1), where success is defined as the ability to mobilize a critical mass to join the effort. The model 7.

(16) consists of six key attributes: (1) Vision and Strategy of the initiative, which is valuable, coherent, flexible and is accepted by the crowd; (2) Human Capital, referring both to the number and quality of the crowd. Training may be required to help develop necessary skills; (3) Infrastructure, such as access to and adoption of the technology; (4) Linkages and Trust formed between individuals and workgroups, which enable the sharing of knowledge and resources. It is argued that crowdsourcing is in essence a people-oriented system, and such linkage is important to sustain the projects; (5) External Environment befitting the objectives of the projects; (6) Motive Alignment, which lies at the core of this model, refers to the extent to which the crowd’s motivation is in line with the purpose of the initiative.. Infrastructure Human Capital. Vision and strategy. Linkages and Trust. Motive alignment of the crowd. External Enviornment. Figure 2.1 Critical Success Factors Model of Crowdsourcing Source: Sharma (2010) Both Malone et al.’s building blocks and Sharma’s success model help to guide organizations through the rollout process of crowdsourcing projects. Focusing on the “crowd”, this present study explores and provides deeper insights into the contributors’ expectations for crowdsourcing initiatives based on an empirical investigation of volunteer experience. 2.1.3 Motivation of the contributing crowd In addition to the organization process, one research area regarding crowdsourcing initiatives that has emerged revolves around the motivations behind crowdsourcing participation (von Krogh & von Hippel, 2006). Howe (2008) observed two shared attributes across crowdsourcing projects: Participants are generally not driven by financial rewards, and they are donating their leisure time—or excess capacity—to the cause. He went on to say that “people derive enormous pleasure from cultivating 8.

(17) their talents and from passing on what they’ve learned to others. Collaboration, in the context of crowdsourcing, is its own reward” (ibid, p.15). Howe’s observation is supported by exploratory researches, in which enjoyment-based intrinsic motivation is a recurring theme. Lakhani & Wolf’s (2005) study examining voluntary contribution to Open Source Software development found that skilled programmers enjoy the sheer pleasure and intellectual stimulation derived from doing what they are good at. In Cámara and Sebastián’s (2013) survey of TED Open Translation Project participants, values, reciprocity, enjoying free time and learning were the highest ranked motivations. Borst (2010), on the other hand, studied the motivation of top performers in four different crowdsourcing projects and argued that depending on the nature of the project, they are driven by an interplay between pure pleasure and the desire for external rewards. 2.1.4 Crowdsourcing translation As illustrated in the previous sections, one of the prominent features of crowdsourcing is the use of volunteers collaborating in a community setting. Unlike community interpreting, where the practice of untrained native speakers acting as language liaisons is a well-established field of study, crowdsourcing translation, or community translation as a social activity is a relatively untouched area (O’Hagan, 2011). Indeed, traditional translation studies are predominantly professional-focused, and amateur translation has triggered concerns over the negative impact on the profession (PérezGonzález & Susam-Saraeva, 2012). However, as volunteer translation activities gradually move towards the center of the socioeconomic scene as a result of the democratization of technology, they have drawn the attention of scholars even in the translation industry. Calling the activity “wiki-translation,” Cronin (2012) for example observed that while the new, interactive medium for content generation and consumption in Web 2.0 is driving up more translation needs, it will continue to reshape the translation profession, turning translation consumers into translation producers. Some practitioners are in fact encouraging professional translators to contribute to this new development by playing process and project management or quality assurance roles (Zetzsche, 2010).. The elements of crowdsourcing are in fact not entirely new to the translation community. Instances of collaborative translation where professional and non9.

(18) professional translators work together can be found historically in the translation of books, and communities of practice where members exchange knowledge are not uncommon among translators (Risku & Dickinson, 2009). Meanwhile, fans of Japanese animations have long devoted their time to “fansubbing,” creating and syncing translated subtitles for their favorite cartoon series (Díaz-Cintas, 2006; Dwyer, 2012). What is unique about crowdsourcing translation, though, is the existence of organizations that systematically use free or relatively cheap labor to fulfill their content localization needs.. However, not all participants of crowdsourcing translation are non-professionals, and not all are unpaid. For this reason, Pym (2011) suggested using “volunteer translators” as the opposite term for professional translators, and O’Hagan (2011) opted for “community translators.” Regardless of their translation training backgrounds, volunteers may be drawn to crowdsourcing projects by a shared desire to contribute to a greater cause (Pérez-González, 2012). As Baker (2009) indicated, activist translators and interpreters may choose to volunteer their time and effort to support certain political cause or to support linguistic diversity. Volunteer translators have also proved to be valuable in times of emergency and in war zones, such as in the aftermath of the earthquake in Haiti, when they helped translate emergency reporting messages from Kreole to English for the relief workers to respond in time (Munro, 2010).. Crowdsourced translation initiatives can be divided into three types: outsourcingdriven (projects initiated by for-profit companies in similar ways they would outsource a task), product-driven (localization of free software for common usage), and cause-driven (projects initiated by not-for-profit organizations for a cause) (McDonough, 2012). While outsourcing-driven projects involve for-profit companies such as Facebook calling for users to localize its interface into different languages, usually to boost user engagement, product-driven initiatives allow translators to make computer programs or open-source software available to a broader user base. Initiatives such as Wikipedia and the TED Open Translation Project (OTP), on the other hand, would fall under the cause-driven category, with clear mission statements to spread knowledge further. McDonough’s (2012) survey on volunteer translators of Wikipedia revealed that making information accessible to other language users and 10.

(19) helping the organization they volunteer for are the top reasons for volunteering (ibid). Similarly, two recent interdisciplinary researches about volunteer motivation of TED OTP also agreed that volunteers participate mainly because they identify with TED’s philosophy and that they want to be involved in TED’s mission of spreading ideas (Cámara & Sebastián, 2013; Olohan, 2013).. Along with Wikipedia and Facebook, the TED Open Translation Project has appeared as a representative example for the “wiki-translation” phenomenon. While the previous two studies focused on volunteer motivation, this research takes a step further and seeks to investigate the main sources of volunteer satisfaction and dissatisfaction. As volunteer satisfaction and motivation are intricately related, this research can be regarded as an extension to previous studies. 2.1.5 TED Open Translation Project The TED Open Translation Project is an initiative launched by the TED Conferences that allows talks available on its website to be translated into different languages by volunteer translators. As a nonprofit organization running under the slogan “Ideas worth spreading,” TED began as a one-off conference in 1984 that aimed to bring people from three areas: Technology, Entertainment and Design. Now covering a wide range of topics delivered in the form of 18-minute presentations by leading practitioners of their fields, TED hosts two conferences annually and makes the talks available on its website for public viewing. In 2009, to bring TEDTalks to a wider audience, the organization collaborated with dotSUB, a browser-based subtitling platform, to create an online translation system for volunteers to translate TEDTalks’ English subtitles under a Creative Commons license. The translation platform was later moved to another subtitling platform, Amara, in 2012. For TED translators, subtitling works in three stages: translation, review and approval, with the first two tasks done by volunteer translators, and the last action completed by Language Coordinators (management roles assigned by TED to volunteers who are active in their local communities). To ensure accuracy of the transcript, English subtitles are generated professionally by TED, and TED Translators can then request to work on a translation or a review task. For each published work, volunteer translators are credited by name. With more than 40,000 talks translated into over 100 languages, TED Open Translation Project is one of the first and most comprehensive translation 11.

(20) crowdsourcing projects done by a media platform2. 2.2 Volunteer and work satisfaction There is little agreement over which theoretical framework is best suited for volunteering studies (Hustinx, Cnaan & Handy, 2010). Moreover, limited research has been done in the sphere of volunteer satisfaction (Galindo-Kuhn & Guzley, 2001). Past literature shows that it is mainly understood as “job satisfaction in the non-paid setting” through long-standing conceptual models derived from physiological or behavioral studies, often applied to explain job satisfaction (Gidron, 1983). Such approach is reasonable, given the similarities between paid and non-paid work experience: A volunteer can undertake the same task under the same context as a fully paid employee.. Yet the differences cannot be neglected. Some scholars argue that volunteers should be regarded as customers of the organization. Since volunteers are not obliged to stick to one organization, they can opt in and opt out anytime (Boezeman & Ellemers, 2009), selecting the most preferred organization to pursue their own goals and objectives (Wisner et al., 2004). Without the lever of pay and punishment, organizations can only seek to address volunteer satisfaction with the job in order to ensure service sustainability (ibid). In this respect, volunteers are analogous to customers “buying the benefits they seek, paying with their time and skills which they can almost invariably take elsewhere” (Wilson & Pimm, 1996, p.37). To understand volunteer expectations and experience, this research incorporates job satisfaction literature in both paid and non-paid settings, with references to marketing studies. In particular, it utilizes the Kano’s model of satisfaction, which has been widely used in both job satisfaction and customer satisfaction studies. 2.2.1 Job satisfaction in the paid work setting Before delving into volunteer satisfaction, it is necessary to explain satisfaction in the paid work setting. As an integral part for the well-being of both the organizations and individuals, job satisfaction is one of the most researched attitudes towards work in organizational studies (Judge & Church, 2002). It has been linked to a variety of 2. Source: www.ted.com/translate. 12.

(21) organizational outcomes, such as performance (Judge et al., 2000; Organ, 1998), turnover (Carsten & Spector, 1987; Hulin, 1968) and attendance (F. J. Smith, 1977). In Total Quality Management literature, employees are regarded as internal customers, whose level of satisfaction is key to the overall quality of the company’s service (Matzler, Fuchs & Schubert, 2004a). Particularly, the importance of employee satisfaction for human resources management has been stressed now that employees are carriers of knowledge and considered valuable assets of the company (ibid). While the effect of work attitudes has been explored as early as 1911 in Taylor’s studies about scientific management, systematic studies of job satisfaction only emerged in the 1930s (Locke, 1976). Since then, a rich body of literature has been devoted to the understanding of job satisfaction (Spector, 1997). Job satisfaction, as Hulin & Judge (2003) noted, has evaluative, emotional and behavioral components, and can be defined from either “affective” or “cognitive” perspectives. The most commonly used definition is contributed by Locke (1976), who described it as “a pleasurable or positive emotional state resulting from the appraisal of one’s job or job experiences” (p.1300). Such definition emphasizes the overall emotional feeling one has toward the job, which can include boredom, anxiety, excitement and more. Implicit to Locke’s definition is the cognitive component, which looks more subjectively at the various facets of job satisfaction. Adopting the cognitive point of view, Smith, Kendall and Hulin (1969), for example, identified job itself, pay, promotion opportunities, supervision and coworkers as five key dimensions for measuring job satisfaction. Meanwhile, some cognitive theorists look at job satisfaction in relative terms. In marketing studies of consumer satisfaction, satisfaction is the degree to which a customer’s experience exceeds his or her expectations (Churchill & Surprenant, 1982). Job satisfaction is therefore the “perceived discrepancy” between what one desires and what one is actually awarded (Locke, 1969). Based on previous attempts to conceptualize the construct, Luthans (2011) summed up the definition of job satisfaction well: it is the inferred emotional reaction to a job situation, driven by the degree experience meets or exceeds expectations, and reflects the worker’s attitudes toward the various attributes of work, for instance, pay, promotions, colleagues, supervision and work itself. 13.

(22) 2.2.2 Job satisfaction theories Many job satisfaction researches share the same theoretical bases with motivation studies. Maslow’s (1943) Hierarchy of Needs is a widely cited theory based on which the underlying drivers of job satisfaction are discussed. According to Maslow, all individuals seek to fulfill the same set of needs—physiological needs (e.g. hunger, thirst), safety needs (e.g. shelter, protection), social needs (e.g. relationships), selfesteem needs (e.g. achievement, recognition) and self-actualization (e.g. inner potential)—in a hierarchical manner. In this conceptual pyramid of five layers, once the basic needs are satisfied, they no longer motivate behaviors, and people go on to pursue higher order needs at the next level. Alderfer (1972) simplified Maslow’s five needs to three basic needs, condensing the first two levels of the hierarchy into Existence needs, the third and fourth levels into Relatedness needs and the last level into Growth needs. He argued that instead of a hierarchy, individuals’ needs should be thought of as a continuum, and may move along in both directions. For example, an employee may regress to social needs when growth needs remain unsatisfied. It is therefore important for employers to recognize their workers’ needs that exist simultaneously. Herzberg et al.’s (1959) Two-Factor Theory is another often-cited theory for explaining employee attitudes. The theory argues that the opposite of satisfaction is not dissatisfaction, but simply “no satisfaction”, since satisfaction and dissatisfaction are controlled by different factors. Through open-ended questions inquiring employees’ negative and positive work experiences, two lists of satisfaction and dissatisfaction factors are concluded (Tietjen, 1998). The “motivators”, which include job related factors such as achievement, recognition, work itself, responsibility and advancement, can lead to job satisfaction. Job dissatisfaction, on the other hand, results from the absence of “hygiene factors”, defined as conditions surrounding the job, such as salary, interpersonal relations, working conditions, company policies and job security. Yet Herzberg’s theory is not without criticism. Later researchers have been unable to replicate Herzberg’s results empirically (Hackman & Oldham, 1975). The research methodology (critical incident technique), which accounts for frequency, instead of. 14.

(23) intensity of pleasant and unpleasant events, may neglect infrequent events that cause a higher level of satisfaction or dissatisfaction (Locke, 1976). The construct’s unipolar continuum of one group of factors only related to satisfaction and one only pertaining to dissatisfaction has also been criticized as arbitrary and a denial of individual differences (Locke, 1976; Matzler et al., 2004a). Locke (1976) instead argued that employees have unique values and may react differently to money or promotion.. To explain individual differences, Locke (1976) contended that job satisfaction should be determined by the discrepancy between what the employees think “should be” and what the actual situation “is now”. Since employees weigh job related factors differently, their assessment of job satisfaction will also differ.. The fact that few groundbreaking theories have emerged in this field since Maslow and Locke’s time (Latham & Pinder, 2005) shows the long-lasting applicability of these theories. For example, Maslow’s and Alderfer’s need structure have led to later motivational theories (Ryan & Deci, 2000) widely used in organizational studies to this day (Boezeman & Ellemers, 2009). Herzberg’s Two-Factor Theory and Locke’s Discrepancy Theory also pave the way for the Kano (1984)’s model of satisfaction, a tool that will be used in this study for understanding sources of volunteer satisfaction and dissatisfaction. 2.2.3 Antecedents and consequences of job satisfaction Organizational researchers are keen on identifying the antecedents and consequences of job satisfaction. Theories investigating the causes of job satisfaction fall into three large categories: Job characteristics theories attribute job satisfaction to the nature of the work itself; dispositional theories see personality traits as the root cause, and interactive theories adopt an integrated approach that takes into account both situational and dispositional factors (Judge & Klinger, 2007). Numerous empirical researches have directly or indirectly confirmed the basic assumptions of job characteristics theories. When asked to evaluate different facets of their job, employees almost always rate work itself is as the most important item, before pay, supervision, promotion and coworkers (Judge & Church, 2002). Furthermore, satisfaction with the work itself also manifests as the most strongly correlated aspect with overall job satisfaction (ibid). 15.

(24) Arguing that intrinsically motivating jobs will lead to high job satisfaction, Hackman and Oldham (1976) proposed the Job Characteristics Model (Figure 2.2). Once the five core characteristics defined in the model are fulfilled, employees will reach critical psychological states, which, in turn, will lead to personal and work outcomes such as job satisfaction. Among the characteristics, “skill variety” (opportunity to utilize different skills and talents), “task identity” (ownership of one’s work) and “task significance” (potential impact the job can create) can lead to experienced meaningfulness of work. “Autonomy”, or the degree to which an employee can decide how to carry out a job, can bring experienced responsibility for work outcomes, and “feedback”, or direct information about the effectiveness of an employee’s performance, ensures he or she has knowledge of results of work activities. Originally a purely situational theory, individuals’ growth need strength was later added as a variable to explain why employees may have different levels of satisfaction given the same job characteristics (Judge & Klinger, 2007).. Core job characteristics. Critical psychological states. Skill variety Task identity Task significance. Experienced meaningfulness of the work. High internal work motivation. Autonomy. Experienced responsibility for outcome of the work. High quality work performance. Knowledge of the actual result of the work activities. High satisfaction with the work. Feedback. Employee growth need strength. Personal and work outcomes. Low absenteeism and turnover. Figure 2.2 Job Characteristics Model (Hackman & Oldham, 1976) Based on discrepancy theory, Wexley and Yukl (1977) proposed a comprehensive. 16.

(25) framework that incorporates job characteristics, personal traits as well as information processing approaches to job satisfaction (Figure 2.3). Positing that job satisfaction results from a comparison between expected work conditions and actual work conditions, this model distinguishes variables that shape employees’ expectations (personal and social variables) from those that determine actual work experience (reward, salary, management and promotion).. Needs Values Personal Traits Expected Work Conditions Comparison with others Reference Groups Previous Work Experience. Rewards & Salary Management Job itself Associates Job Security Promotion. Job Satisfaction. Actual Work Conditions. Figure 2.3 Antecedents of Job Satisfaction (Wexley & Yukl, 1977) In regard to the outcomes, both positive and negative satisfaction is linked to a myriad of work behaviors, including work performance (Judge, Thorsesen, Bono & Patton, 2000), attendance (F. J. Smith, 1977; Wegge, Schmidt, Parkes & van Dick, 2007), turnover (Spector, 1987) and organizational citizenship (Organ, 1988). Most significantly, it is consistently related to individual’s subjective well-being, or, in other words, satisfaction with life (Judge & Klinger, 2007). Despite the large array of related outcomes, the correlation between positive job satisfaction and performance typically lies in the .15-.35 range (ibid). Against the conclusion made by some managers that dismisses job satisfaction as trivial (Saari & Judge, 2004), Organ (1988) argued that the failure to find a strong relationship is often due to a narrow definition of work performance, and correlation can be improved when specific attitudes are measured against specific outcomes. After refining the sampling and measuring errors of a large body of past researches, Judge et al. (2000) found a higher average. 17.

(26) correlation, and also observed that job satisfaction is more predictive of performance when the job is professional or sophisticated. In addition to ensuring employee satisfaction, employers need to avoid dissatisfaction as well. D. Farrell (1983) has pointed out that employees respond to dissatisfaction by constructively voicing out their opinions, or destructively neglecting work or exiting the company.. Job characteristics attributed as antecedents of job satisfaction form the basis of various measures of job satisfaction, used as questionnaire items to solicit employees’ assessment of their satisfaction level. In this research, factors related to both work itself and work conditions will be explored to understand volunteers’ expectation for the work, and then to understand their actual experiences. 2.2.4 Measures of job satisfaction Two types of instruments exist for the measurement of job satisfaction based on employees’ reported feelings toward their jobs (Robbins, 1993). The first, global satisfaction, refers to employees’ overall feeling about their job, measured usually by asking “Overall, how satisfied are you with your job?” The second, faceted satisfaction, assess feelings about specific job aspects. The most extensively validated facet-based measure of job satisfaction is the Job Descriptive Index (JDI), which appraises employees’ response to five job areas: pay, promotion, coworkers, supervision and work itself (Smith et al., 1969). Even though no instrument can claim to encompass all variables of job satisfaction, and the sum of various facets does not equal to overall satisfaction (Scarpello & Campbell, 1983), both types of measures can reliably assess the level of job satisfaction (Saari & Judge, 2004). For organizations wishing to explain organizational issues such as high turnover, facetbased measures are useful for identifying specific areas for improvements and best leverage limited resources for the highest level of satisfaction. 2.2.5 Application of the Kano Model The Kano’s Model of Satisfaction (1984) is another useful tool for measuring employee expectations. Originally devised to classify product or service attributes based on how they are perceived by customers and how they may affect customer satisfaction (Ullman, 1997), it assumes satisfaction derives from a cognitive comparison of expectations and perceived performance (Mikulić, 2007). Based on. 18.

(27) Herzberg’s (1959) Two-Factor Theory, which is widely used to explain both employee and consumer behaviors, the Kano Model posits that not all customer requirements form a linear relationship with the level of customer satisfaction. The fulfillment of some factors will not increase the level of satisfaction, but the lack thereof may trigger dissatisfaction. In short, the opposite of satisfaction is not dissatisfaction, and vice versa. While Herzberg is criticized for assigning the factors a priori, Kano’s model takes into account contextual variations and explores individual preferences through questionnaire surveys (Matzler et al., 2004a). A straightforward approach to applying the Kano Model is to ask customers to rate their level of satisfaction for the presence and absence of each attribute: “How would you feel if the product has this attribute?” and “How would you feel if the product did not have this attribute?” Based on the answers to these two sets of questions, Kano’s model takes Herzberg’s motivators and hygiene factors a step further and makes a classification of four major factors, each with a different impact on satisfaction. The following presents the key attributes based on Kano literature (Berger et al., 1993; Matzler & Hinterhuber, 1998; Mikulić, 2007). These attributes are named differently in quality service and customer satisfaction researches, most commonly referred to as “quality attributes”, “customer requirements” or “satisfaction factors”.. Figure 2.4 The Kano’s model of customer satisfaction (Berger et al. 1993). 19.

(28) . Must-have factors do not boost satisfaction if present, but will incur dissatisfaction if absent.. . One-dimensional factors boost satisfaction if present, and will incur dissatisfaction if absent.. . Attractive factors boost satisfaction if present, but will not incur dissatisfaction if absent.. . Indifferent factors have no effect on satisfaction or dissatisfaction.. Must-have factors can be seen as basic requirements, or market entry threshold, that are expected by customers. Fulfilling requirements of these factors does not create differentiation opportunities, but is necessary for avoiding customer dissatisfaction. That is to say, negative performance on these attributes has a greater impact on satisfaction than positive performance. For example, car brakes are taken for granted, and will only be noticed when it is dysfunctional.. For customer requirements that fall under the one-dimensional category, customer satisfaction is proportional to how functional the product or service is. The better the product or service performs on this attribute, the more satisfied the customers. The worst the product or service performance, the less satisfied the customers. An example of a one-dimensional attribute would be warranty period of a car.. Attractive factors, or excitement attributes, are usually inexplicit or unexpected needs of the customers, but can result in high levels of satisfaction. In a competitive environment, companies that offer attractive attributes to address customers’ unspoken needs can create a competitive advantage. Using the car as an example again, attractive factors would be in-dash GPS system in a car.. Indifferent factors have little or no consequence to the customer, and do not affect purchase decisions. The original Kano questionnaire include two more factors— “questionable” and “reverse” attributes, which result from incorrect wording and hypothesis on the part of the questionnaire designer, but are often removed to avoid confusion (Matzler et al., 2004a).. The Kano model is one of the most popular quality models, used by product 20.

(29) designers, marketers and employees to identify key drivers of customer satisfaction and dissatisfaction (Mikulić, 2007). While the original Kano Method, which requires respondents to answer both functional and dysfunctional questions, has been widely applied in different areas, for example on web-community service (Kuo, 2004), tourist destination (Pawaitra & Tan, 2003) and e-service (Nilsson-Witell & Fundin, 2005), variants of the Kano model is also adopted and verified in the sphere of employee satisfaction (Eskildsen & Kristensen, 2006; Matzler et al., 2004a; Martensen & Grønholdt, 2001; Peters, 2005), all based on its key spirit—“the relationship between attribute-level performance and overall satisfaction is asymmetric” (Matzler, Bailom, Hinterhuber, Renzl & Pichler, 2004b, p.271). Compared to traditional employee satisfaction surveys that assume all job facets are one-dimensional, the Kano model has the advantage of allowing organizations to understand employees’ perception of different job dimensions and identify improvement areas (Matzler et al., 2004a). For example, the Importance-Performance Analysis (IPA) (Martilla & James, 1977) is another popular instrument for measuring job satisfaction. It analyzes employee-rated level of importance of different jobrelated factors against employee satisfaction to create a mapping of priority improvement areas. However, the IPA does not consider the two-dimensional quality. As Kuo, Chen and Deng (2012) pointed out, both “Must-be” and “Attractive” factors in the Kano model would fall into concentration areas without distinguishing which one requires more immediate improvement. With results from the Kano analysis, organizations can take actions to fulfill all must-have requirements, be competitive on one-dimensional requirements and differentiate through attractive factors (Matzler & Hinterhuber, 1998). Therefore, by categorizing job attributes into different Kano factors, this method is used in this research to identify key volunteer requirements for crowdsourcing translation projects. 2.3 Volunteer motivation and satisfaction In the non-paid work setting, why people are willing to devote their time and energy to providing services for no financial rewards has long been a topic of interest for scholars in social psychology as well as economics studies (Hustinx et al., 2010). Traditionally, volunteerism is often linked to psychological altruism, which means that people act selflessly for the sole purpose of increasing public welfare (Gidron, 1978). However, as economist Andreoni (1990) pointed out in his model of “impure 21.

(30) altruism,” people derive a sense of satisfaction—what he describes as “warm glow”— from giving. Scholars of social behavioral science also look beyond complete selflessness for motivations to volunteer. D. H. Smith (1981) went on to suggest that satisfaction is not merely a by-product but expectation for volunteers. Volunteer motivations are commonly categorized into two or more dimensions. Gidron (1978), for example, distinguished “intrinsic rewards” from “extrinsic rewards. Cnaan and Goldberg-Glen (1991) reviewed an extensive body of relevant literature and compiled 28 items of volunteer motivation. Their own empirical research concluded that a combination of multiple motives is at work when people volunteer, including altruistic motives (“the opportunity to do something worthwhile”) and egoistic ones (“volunteering for others makes me feel better about myself”). Clary et al. (1998), on the other hand, took a functional approach and pinpointed six broad functions served by volunteering: Values (To serve humanitarian values), Understanding (To learn), Social (To form relationships with others), Career (To gain career-related experience), Protective (To escape from negative feelings) and Enhancement (To enhance positive psychological development). These studies on motivation, whether descriptive or empirical, often indicate a link between volunteers’ motivation, satisfaction and intent to stay. Volunteers will continue to work for the organization as long as “the experience as a whole is rewarding and satisfying to their unique needs” (Cnaan & Goldberg-Glen, 1991). Farrell, Johnston and Twynam (1998) drew on consumer behavior literature and suggested that volunteers will remain the same way as consumers stick to a particular product or a service because of the satisfying experience they enjoyed previously. This linkage is verified by Clary et al. (1998) in their development of a Volunteer Functions Inventory to predict volunteer satisfaction as well as their intent to stay. Their empirical study showed a positive correlation between commitment to volunteering and how strongly the volunteers feel the benefits they received matches their functional motivations (ibid). That is, if volunteers are satisfied and their motivational needs are met, they will most likely continue to volunteer in both the near-and long-term future. It is worth mentioning here that reviewing through literature, one can find a general tendency to confuse work motivation with job satisfaction (Locke & Latham, 2004),. 22.

(31) with motivation used as a synonym to “motivational antecedents” of job satisfaction. This present research understands the intricacy of the two concepts, and agrees with the common definition of work motivation as what “arouses, energizes, directs and sustains behavior and performance” (Luthans, 2011). In addition, Ryan and Deci’s (2000) definition is adopted to further differentiate intrinsic motivation—what drives people to do an activity for its inherent satisfactions rather than for some separable consequence, from extrinsic motivation—what drives people to engage in an activity in order to gain separable outcomes. Therefore, workers can be motivated because the work itself is pleasant, challenging (Horwitz, Heng & Quazi, 2003) and because of the financial rewards, security it promises (Ryan & Deci, 2000). These motivational factors have been reported as predictors of job satisfaction (Boezeman & Ellemers, 2009; Wisner et al., 2004), and as inextricably linked as the two concepts are, satisfaction at job can in turn motivates people to continue working (Rao, 2011). Along this line of thoughts, this study argues that satisfaction factors will inevitably overlap with motivational factors, but will not be limited to the latter. This is exemplified in the instrumentation for measuring both job satisfaction and volunteer satisfaction. 2.3.1 Measures of volunteer satisfaction Even though volunteers may gain satisfaction from having their motivational needs fulfilled, their motivation and satisfaction cannot be measured on the same scale. Contextual factors such as work environment may not be the reasons why volunteers choose to participate, but will very likely affect their level of satisfaction. Therefore, Gidron (1983) categorized sources of satisfaction into “content-factors” (actual work performed) and “context-factors” (work situation).. However, while measurements of job satisfaction in traditional paid work settings abound, relatively few researches are dedicated to volunteer satisfaction. Many agencies carry out satisfaction surveys to their volunteers on a regular basis, often without a resilient measurement instrument (Galindo-Kuhn & Guzley, 2001). To fill the gap, Galindo-Kuhn and Guzley (ibid) developed the Volunteer Satisfaction Index (VSI) to identify predictors of volunteers’ intention to remain based on previous satisfaction literature. The instrument proposes five dimensions of satisfaction factors. 23.

(32) derived from an extensive body of literature on volunteer satisfaction, which also form the basis of this research’s questionnaire design. The job dimensions are: The work assigned to volunteers (Work Assignment); volunteer’s perception of the impact they are making (Participation Efficacy); educational and emotional support provided by the organization (Organizational Support); the flow of information and feedback from the organization to the volunteers (Quality of Communication) and the relationships developed with peer volunteers and with paid staff (Group Integration). Each dimension consists of 7 to 8 questions to which the respondents indicate their level of satisfaction on a seven-point Likert scale. The validity of the VSI is tested on 327 volunteers in their study, who reported high levels of satisfaction, with “participation efficacy” and “group integration” as predictors of intent to remain. The model has also been adapted in studies in different cultures and settings with proven reliability (e.g. Wong, Chui & Kwok, 2011). 2.4 Chapter summary Literature on crowdsourcing initiatives, job satisfaction and volunteer satisfaction together forms the conceptual framework of this study. Due to the similar nature of volunteers and customers, organizations of volunteering projects should seek to fulfill the requirements of their volunteers. This validates the adoption of the Kano’s model of satisfaction, which can give organizations an indication of what satisfies and dissatisfies volunteers, facilitating the design or improvement of volunteering projects. Two key concepts from literature reviewed form the basis of this study’s research design: 1) Feelings of satisfaction and dissatisfaction derive from the gap between expectation and actual experience, and 2) different attributes can have asymmetric relationship with overall satisfaction.. 24.

(33) Chapter 3. Methodology 3.1 Research design For organizations with limited resources, it is crucial to understand what experience they should create for their voluntary workforce to ensure its sustainability. Naturally, to achieve volunteer satisfaction, there are various requirements an organization has to fulfill. However, satisfaction is not always proportional to the level of fulfillment— higher level of fulfillment does not entail higher employee satisfaction (Matzler & Hinterhuber, 1998). In trying to understand the antecedences of volunteer satisfaction, it is based on this assumption of non-linearity that this research is designed. This study aims to answer the following research questions: 1. What are TED Translators’ views on the key satisfaction factors for an online volunteer translation project? 2. How well does the TED’s Open Translation Project perform along different satisfaction factors? 3. Does different background variables contribute to differences in volunteers’ perceived importance of key satisfaction factors? Though originally developed for product development projects, the Kano’s model of customer satisfaction has proven to be a useful tool for evaluating employee satisfaction (Martensen & Grønholdt, 2001; Matzler et al., 2004a), offering more insights into the different effects of quality attributes. This study employs the Kano method proposed by Matzler and Hinterhuber (1998), which includes a twodimensional questionnaire followed by a customer ranking of individual product criteria. Following Miles and Huberman’s (1994, p.41) suggestion, this study incorporates both qualitative and quantitative approaches, alternating between the two during different research stages. While large-scale questionnaire is necessary to acquire sufficient data points for analysis, qualitative interviews serve to reveal the “Whys” behind the data. To fully leverage the strengths of both, exploratory expert interviews, mass questionnaire surveys and in-depth interviews were administrated sequentially for this study.. 25.

(34) 3.2 Instrumentation 3.2.1 Expert interviews Expert interview is a unique form of semi-structured interview, in which the focus is not on the interviewee per se, but their expertise in a specific field (Meuser & Nagel, 1991). It is commonly used during the exploratory phase of the project to identify specific research questions. When trying to analyze the needs of research targets, it can be considered “arrogant” to bring in a set of predetermined questions (Brown, 2001). Therefore, in devising the questionnaire items for volunteer satisfaction, this study engaged three active TED Language Coordinators to share their views on volunteer satisfaction factors for online translation platforms. Expert A is TED’s Localization and Community Manager as well as a Language Coordinator for Polish. Expert B is a TED Language Coordinator for Traditional Chinese, and Expert C is a Spanish Language Coordinator and an Associate Professor of Applied Linguistics in the University of Cologne. All interviews were conducted through VoIP services.. As the interviews are exploratory by nature, only two basic questions were asked in order to solicit a list of qualities about online crowdsourcing translation projects that the experts consider necessary: 1) What do you think are the key attributes an online volunteer translation project should have? 2) Based on your experience, what has TED offered its volunteer translators to ensure volunteer satisfaction?. The list of qualities provided by the experts were recorded and crosschecked for the most mentioned items. Three common themes emerged from the responses to the first question: content, community building and communication. Expert A noted that volunteers translate certain materials because they identify with the content and want to share them with their local audience. Expert B agreed that the content should be interesting, inspiring or something the volunteers can relate to.. Volunteer community or a sense of belonging is another key element. Expert B stressed the importance of having a “democratic” community, in which everyone can contribute their ideas and opinion. Forming friendship through the project, as Expert C mentioned, makes volunteering a rewarding experience.. 26.

(35) Experts also said that a volunteering program should provide channels for volunteers to communicate with staff and peers easily. All experts reported miscommunications or lack of communication between translators and reviewers as a major source of dissatisfaction. Translators sometimes find their work being edited to a great extent without having been contacted by the reviewers.. In regard to the second question, Expert A pointed out that over the past one year, TED has made significant efforts to strengthen the volunteer community, including setting up Facebook pages for all volunteer translators and for individual language groups. These community pages facilitate the flow of communication between TED staff and volunteers as well as among volunteers. In addition, active volunteers are regularly invited to TED conferences and Translators’ workshops, which, according to expert C, make the volunteers feel recognized and appreciated.. The attributes identified by the experts is in line with key sources of satisfaction in the literature, and will be added under Galindo-Kuhn and Guzley (2001)’s proposed dimensions in the Volunteer Satisfaction Index to develop a multi-faceted questionnaire for the understanding of volunteer expectation and satisfaction. 3.2.2 Online questionnaire A questionnaire consisting of three parts was developed based on relevant literature and experts’ input. The first part includes questions about the respondents’ background information. The second part is designed for Kano analysis, which contains a list of faceted satisfaction factors stated positively and negatively for the respondents to indicate their reactions. The third part uses the same list to gauge TED OTP’s performance along each factor. The complete questionnaire can be found in Appendix I. 3.2.2.1 Background questions The first part seeks to answer the following question: Who are these volunteer translators and why do they volunteer? Background questions include 10 questions about age, gender, occupation, working languages and other personal information. Volunteers are asked to select at most two working languages from a drop-down list. In order to differentiate active translators from less active ones, respondents are also. 27.

群眾外包翻譯計畫的志工滿意度研究： 以TED開放翻譯計畫為例

群眾外包翻譯計畫的志工滿意度研究：以TED開放翻譯計畫為例