Translation-Mediated Organization Discourse in Cyberspace: A

TRANSLATION-MEDIATED ORGANIZATION DISCOURSE IN CYBERSPACE: A

CONTRASTIVE CONVENTION ANALYSIS OF SELECTED LOCALIZED AND

NON-LOCALIZED ENGLISH-LANGUAGE ORGANIZATION WEBSITES

A dissertation submitted

To Kent State University in partial

Fulfillment of the requirements for the

Degree of Doctor of Philosophy

Bin Liu

August 2018

Dissertation written by

Bin Liu

B.Eng., Nanjing University of Science & Technology, 2005

M.Eng., Southeast University, 2008

Ph.D. Kent State University, 2018

Approved by

______, Chair, Doctoral Dissertation Committee Keiran Dunne

______, Members, Doctoral Dissertation Committee Greg Shreve

______Erik Angelone

______Sara Newman

______Janet Meyer

Accepted by

______, Chair, Department of Modern & Classical Language Studies Keiran Dunne

______, Dean, College of Arts and Sciences James L. Blank

TABLE OF CONTENTS

TABLE OF CONTENTS ...... iii

LIST OF FIGURES ...... vii

LIST OF TABLES ...... viii

ACKNOWLEDGMENTS ...... xii

I. Introduction: Context and Motivation ...... 1

1.1 A Theoretical Overview: Textual Convention in Website localization ...... 2

1.1.1 “The most conventional digital genre”—Websites...... 2

1.1.2 Conceptualizing localization and translation in the context of cyberspace...... 5

1.1.3 Charting the territory of website localization with the map of Translation Studies. 11

1.2 The Research Topics under Study ...... 13

1.2.1 Counteracting some current trends in the studies of website localization...... 13

1.2.2 Exploring Industry-specific influence on localized websites ...... 19

1.2.3 Searching for a variant of written English in web-mediated organization discourse:

Source language-specific influence on localized websites ...... 20

1.3 Summary ...... 22 II. Scope and Significance ...... 24

2.1 Research Questions and Basic Assumptions...... 26

2.1.1 To what extent are navigational terms and phrases standardized in the selected

localized websites under study? ...... 27

2.1.2 To what extent do the localized website texts embody language-specific features? 28

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2.1.3 Is there any industry-specific conventional feature of localized websites that differentiates themselves from their counterparts from a different industry? ...... 29

2.1.4 Does a variant of English exist in websites localized from Chinese? ...... 31

2.2 Significance of the Current Study ...... 32

2.2.1 Providing language- and culture-specific references for localization practice and evaluation...... 34

2.2.2 Decoding the language of localized websites: An undertaking to enrich the studies of applied Internet linguistics...... 36

2.2.3 Addressing business, economic, and social concerns: Language planning and management...... 37

2.2.4 Pedagogical implications...... 40

2.3 The Structure of the Dissertation ...... 43

2.4 Summary ...... 44 III. Research Approach and Methodology ...... 46

3.1 Instrument ...... 49

3.2 Sample Selection and Data Validation ...... 52

3.3.1 Terms and lexis...... 58

3.3.2 Syntax, grammar and discourse...... 59

3.3.3 Industry- and language-specific effect...... 60

3.4 Summary ...... 61 IV. Results and Analysis ...... 61

4.1 Step 1 of Phase 1: Paired Comparisons ...... 63

4.1.1 LSP: Pactera vs. TransPerfect...... 63

4.1.2 Ecommerce: AliExpress (Alibaba) vs. Amazon...... 71

4.1.3 University: Tsinghua vs. UC Berkley...... 76

4.1.4 Government: Beijing vs. Washington DC...... 82

4.1.5 Tourism destination: Beijing vs. Washington DC...... 87

4.1.6 Cross-industry comparison...... 91

4.2 Step 2 of Phase 1: Grouped Comparison ...... 93

4.2.1 LSP...... 93

4.2.2 University...... 96

4.2.3 Government...... 98

4.2.4 Tourism destination...... 99

4.2.5 Cross-industry comparison...... 102

4.3 Phase 2: A Statistical Exploration of Industry- and Language-specific Effects .... 104

4.4 Summary ...... 111 V. Discussion and Conclusion ...... 112

5.1 Instrument ...... 112

5.2 Data ...... 115

5.2.1 Navigational text: The buttress of website convention...... 116

5.2.2 Content text: The emergence of convention...... 119

5.3 Analytical Framework ...... 120

5.4 From Content to Content Strategy: Website Analysis as a Booming Field of

Interdisciplinary Collaboration between Academia and Industry ...... 121

5.5 Concluding Remarks ...... 123 REFERENCES ...... 126

APPENDICES ...... 142

A. The Websites Selected for Grouped Comparisons at Step 2 of Phase 1 ...... 142

B. The Lexical Items of Different Sections of LSP Websites (L: Localized website;

NL: Non-Localized website) ...... 146

C. The Lexical Items of Different Sections of University Websites (L: Localized website;

NL: Non-Localized website) ...... 147

D. The Lexical Items of Different Sections of Government Websites (L: Localized

website; NL: Non-Localized website) ...... 148

E. The Lexical Items of Different Sections of Tourism-destination Websites (L: Localized website; NL: Non-Localized website) ...... 149

F. The Websites Selected for Phase 2 (L: Localized; NL: Non-Localized) ...... 150

LIST OF FIGURES

Figure 1. Editor Window of a CAT Tool, SDL Trados Studio 2014 ...... 41

Figure 2. Phase Chart ...... 49

Figure 3. Process Flowchart ...... 49

Figure 4. Summary Page of Statistical Decision Tree ...... 52

Figure 5. The Prototypical Superstructure of Corporate Websites in Jiménez-Crespo’s study

(Jiménez-Crespo, 2009)...... 56

Figure 6. Word Clouds for the Two LSP Website Groups ...... 96

Figure 7. Word Clouds for the Two University Website Groups ...... 98

Figure 8. Word Clouds for the Two Tourism-destination Website Groups ...... 102

Figure 9. Input Parameters and Output Calculation Results of G*Power ...... 105

Figure 10. Profile Plots ...... 110

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LIST OF TABLES

Table 1. The Selected Localized and Non-Localized English Websites for Step 1 of Phase 1 53

Table 2. The Selection Criteria of Localized and Non-Localized English Websites for Step 2

of Phase 1 ...... 55

Table 3. The Items of Interest under Study in Phase 1 and 2 ...... 60

Table 4. Crosstab Template Listing All the Textual Features under Analysis for the Chosen

LSP Website Sections...... 64

Table 5. The Lexical Items of Different Sections of Pactera and TransPerfect Websites ...... 66

Table 6. Distinct Sections in Paired LSP-website Comparison ...... 67

Table 7. Lexical Density of the LSP Website Sections Available for Content-text Comparison

...... 69

Table 8. The Average Sentence Length of the LSP Website Sections Available for Content-

text Comparison ...... 69

Table 9. The Relative Frequency of First- and Second-person Sentences in the Website

Sections Available for Content-text Comparison ...... 70

Table 10. Crosstab Template Listing All the Textual Features under Analysis for the Chosen

Ecommerce Website Sections ...... 72

Table 11. The Lexical Items of Different Sections of AliExpress and Amazon Websites ...... 73

Table 12. Distinct Sections in Paired Ecommerce-website Comparison ...... 75

Table 13. Lexical Density of the Ecommerce Website Sections Available for Content-text

Comparison ...... 75

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Table 14. The Average Sentence Length of the Ecommerce Website Sections Available for

Content-text Comparison ...... 76

Table 15. The Relative Frequency of First- and Second-person Sentences in the Ecommerce

Website Sections Available for Content-text Comparison ...... 76

Table 16 Crosstab Template Listing All the Textual Features under Analysis for the Chosen

University Website Sections ...... 77

Table 17. The Lexical Items of Different Sections of Tsinghua and UC Berkeley Websites .. 78

Table 18. Distinct Sections in Paired University-website Comparison ...... 80

Table 19. Lexical Density of the University Website Sections Available for Content-text

Comparison ...... 81

Table 20. The Average Sentence Length of the University Website Sections Available for

Content-text Comparison ...... 81

Table 21. The Relative Frequency of First- and Second-person Sentences in the University

Website Sections Available for Content-text Comparison ...... 82

Table 22. Crosstab Template Listing All the Textual Features under Analysis in the Chosen

Government Website Sections ...... 83

Table 23. The Lexical Items of Different Sections of Localized and Non-localized

Government Websites ...... 84

Table 24. Distinct Sections in Paired Government-website Comparison ...... 85

Table 25. Lexical Density of the Government Website Sections Available for Content-text

Comparison ...... 85

Table 26. The Average Sentence Length of the Government Website Sections Available for

Content-text Comparison ...... 86

Table 27. The Relative Frequency of First- and Second-person Sentences in the Government

Website Sections Available for Content-text Comparison ...... 86

Table 28. Crosstab Template Listing All the Textual Features under Analysis for the Chosen

Website Sections ...... 88

Table 29. The Lexical Items of Different Sections of Beijing and DC Tourism Websites ...... 88

Table 30. Distinct Sections in Paired Tourism-website Comparison ...... 89

Table 31. Lexical Density of the Tourism Website Sections Available for Content-text

Comparison ...... 90

Table 32. The Average Sentence Length of the Tourism Website Sections Available for

Content-text Comparison ...... 90

Table 33. The Relative Frequency of First- and Second-person Sentences in the Government

Website Sections Available for Content-text Comparison ...... 91

Table 34. Summary of Paired Comparison ...... 92

Table 35. Four Features Related to Content Text for the Grouped Comparison of LSP

Websites ...... 95

Table 36. Four Features Related to Content Text for the Grouped Comparison of University

Websites ...... 98

Table 37. Four Features Related to Content Text for the Grouped Comparison of Tourism-

destination Websites ...... 101

Table 38. Summary of Grouped Comparison ...... 102

Table 39. The Presence of Gateway Feature ...... 103

Table 40. Descriptive Statistical Results ...... 107

Table 41. Multivariate Tests for the Independent Variables ...... 108

Table 42. Tests of Between-subject Effects ...... 109

Table 43. The Industry- and Organization-specific Website Sections ...... 117

ACKNOWLEDGMENTS

This work would not have been possible without the financial and intellectual support

of PhD Fellowship program offered by the Department of Modern and Classical Language

Studies at Kent State University. I am especially indebted to Dr. Keiran Dunne, Chair of the

Department of Modern and Classical Language Studies and also my dissertation advisor, Dr.

Brian Baer, the former graduate coordinator, and Dr. Kelly Washbourne, who have been

supportive of my academic and career goals and who have showed their unfailing patience in

giving inspiring comments and suggestions on my research projects to help me pursue those

goals.

On the way to honing my teaching and research skills, I would like to thank the

following professors since they have set an amazing example for me during my PhD studies:

Dr. Greg Shreve and Dr. Sue Ellen Wright, who have kindly shared with me their great insights

on translation industry and practice; Dr. Françoise Massardier-Kenney and Dr. Carol Maier, who have introduced me to the fascinating fields of feminist translation studies and translator studies; Dr. Erik Angelone and Dr. Isabel Lacruz, who have facilitated exciting discussions and demonstrations of empirical methods in translation studies; and Dr. Judy Wakabayashi, who showed me how intellectually uplifting life can be for a historian of translation and translation studies.

I am grateful to all of those with whom I have had the pleasure to work during this project. Each member of my Dissertation Committee has provided me extensive professional guidance and taught me a great deal about research. I would especially like to thank Ms.

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Kristin Yeager, the manager of statistical consultation at Kent State University Library, who helped me learn to enjoy an exploratory journey of leading statistical analysis tools.

Last but not least, I would like to thank my parents, Ms. Yihong Wu and Mr. Xiaozhong

Liu, whose love and guidance are with me whenever I make any life choice. Most importantly,

I want to thank my loving and supportive husband, Mr. Jie Peng, and my wonderful son,

Melburn, who provide unending inspiration.

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I. Introduction: Context and Motivation

Ever since its emergence, localization has intertwined with translation to serve

as an essential part of multilingual information production and management. Striving

to approach localization from a product-oriented perspective, the dissertation conducts

a convention analysis comparing localized and non-localized English websites of

selected Chinese and American organizations, including commercial and nonprofit

ones. The comparison hopes to present empirical evidence for Pym’s (2011) assertion

that Chinese website texts localized into English often maintain their original genre

conventions. This should in turn highlight the observation that the English-mediated cyberspace is enriched by Chinese culture, among others, with its own style of electronic interaction. To begin with, this introductory chapter formulates and presents the rationale for studying website localization, in particular the convention analysis of localized websites. The reasoning process is then followed by the identification of relevant literature gaps as well as the main research topics to be addressed in subsequent chapters.

The overall working hypothesis for the dissertation is that localized English-

language websites show distinctive textual-linguistic features, both at the macro- and micro-structural level when compared with non-localized counterparts. To empirically test this hypothesis, the dissertation will compare the interface texts and content texts of selected localized websites with those of comparable non-localized websites (see

Chapter 2 and 3 for research scope and methodology). This chapter is mainly designed for laying the theoretical groundwork.

1.1 A Theoretical Overview: Textual Convention in Website localization

As the first step of contextualizing the current study, this section begins by illuminating the significance of studying the textual conventions of websites. Then, the conceptual linkage between localization and translation is articulated from both industry and academic perspectives before a discussion of the feasibility of studying a “new translation modality” (Jiménez-Crespo, 2009, p. 79), website localization, within the context of translation studies. It is further contended that both theory and practice of website localization can benefit from the existing body of knowledge in translation studies. This section serves as a theoretical prelude to the relevant research topics that are of interest for the current study.

The research topics to be covered are presented in Section 1.2.

1.1.1 “The most conventional digital genre”—Websites.

Conventions, including those of websites, can be viewed as the building blocks of genres, and convention analysis contributes to an informed understanding of a specific genre.

A genre, as defined by Miller (1984), refers to a conventional category of discourse based on the large-scale typification of rhetorical action; as action, it acquires meaning from situation and from the social context in which that situation arose. While this general definition of genre highlights the importance of action and situation in understanding genre, Hatim and

Mason’s (1990) conceptualization of genre has most relevance to translation studies: “a conventionalized form of text which reflects the functions and goals involved in particular social occasions as well as the purposes of participants in them.” This echoes the functional

and sociocultural approach to translation, including skopos theory. The notion of convention, in translation studies, has been defined as implicit or tacit non-binding regulation of behavior,

“based on common knowledge and on the expectation of what others expect you to expect from them (etc.) to do in a certain situation” (Nord, 1991a, p. 96). Along this line, website conventions can be viewed in translation studies as non-binding features as embodied in a website product, in particular website text, that are expected to fulfill the intended purposes of the website.

Website conventions can be stabilizing and flexible at the same time; they can be stabilizing in facilitating an understanding of web-mediated communication in spite of the ebb and flow of technology, while they can also be flexible in promoting a dynamic understanding of how technology influences web mediation over time. As a web-mediated digital genre, a website structures communication by creating shared expectations about the form and content of the interaction, thus easing the burden of production and interpretation with conventionalized features.

The overall conventionalization of websites as a digital genre has been intuitively or empirically acknowledged in previous publications, including Jiménez-Crespo’s study (2011, p. 5), as quoted in the heading of this subsection (1.1.1). The current study extends these discussions into the context of localization. Symonenko (2007, p. 29) identifies a trend towards greater similarity in the organization of website content, or content structure, and he attributes this conventionalization to standardized industry practices of information architecture and website design. Regarding the content itself, guidebooks or other publications on web design typically specify that web writing requires light style (use of

simple sentences, and discourse organization in short lexis), conciseness (less information to

process), one idea per paragraph, the inverted pyramid style (from main information to

details), and typographic features enhancing scanning (Carrada, 2000). Selected features like

these in their operationalized forms are chosen as the object of study in the dissertation,

which aims at exploring the conventions of localized organization websites with a textual-

linguistic approach.

The call for greater informed flexibility in industry practice also points to the

significance of empirically exploring textual conventions in website localization. Arguably,

adapting the textual structure to the prototype expected by the target discourse community is

a consideration critical to localizing any website, and the same can be said of the expected

terminological and phraseological convention of specific web genres (Nord, 2014). Jiménez-

Crespo (2010, p. 187) argues that intercultural differences in the prototypical structures of

textual genres are a frequent problem in most translation processes, thus posing a challenge to

translator-localizers. Another challenge in localization practice is that the intersection of

technology and translation normally forces the translator to maintain the fixed super- and

macro-structure of digital texts, that is, the underlying back-end coding structure and its screen presentation.

The three generic dimensions conceived by Hatim and Mason (2014), formal aspects

(conventionalized forms), sociocultural aspects (social occasions) and cognitive aspects

(purposes of the participants), are extremely important for understanding website complexity

in different languages and cultures (Borja, Izquierdo, & Montalt, 2009, p. 62). Are the formal

aspects or conventionalized forms of websites culture-neutral? In other words, do websites

exhibit identical conventional features despite their different national and language origins? Is

there any factor in action that leads to or influences the identified conventionalization or

deviation? Localization has thus become an intriguing avenue for such cross-cultural

comparisons where localized and non-localized websites presented in the same language are

examined side by side to provide preliminary answers to these questions.

Cultural, linguistic, text-type and genre adaptations have been considered a central

notion in the conventional linguistic, communicative and functionalist approach, whereas

technical adaptations are believed to be a defining feature of localization (Jiménez-Crespo,

2013, p. 16). In web localization, however, it can be argued that quality is sustained largely

by non-technical components, given the much wider range of textual, discursive and

communicative problems found in this area. Jiménez-Crespo (2013, p. 106) attributes this to

the large number of textual types and genres potentially present in web genres, requiring an

approach closer to other translation types and modalities. This genre embeddedness in web-

mediated communication also underscores genre analysis as a solid foundation for research

and training efforts in web localization (Jiménez-Crespo, 2013, p. 3).

Before jumping into the discussion of website localization, it is necessary to review

the conceptual development of localization first.

1.1.2 Conceptualizing localization and translation in the context of cyberspace.

Localization (sometimes also referred to as its numeronyms, “L10n”) is a relatively young phenomenon in the field of language services. Its roots can be traced back to the first attempts at translating software in the 1980s (Esselink, 2000, p. 5), which were driven by the interests of large US-based multinational software publishers in opening new markets for

their products (Schäler, 2007, p. 120). As the historical development of localization in Ireland demonstrates, the presence of a large localization industry in a country can be a deciding factor in its economic and social development (Schäler, 2007).

There have been quite a few attempts at defining localization in academic literature.

According to Jiménez-Crespo (2009, p. 79), localization is “a technological, textual, communicative and cognitive process by which interactive digital texts are adapted for their use in a different cultural and linguistic context of reception.” Deviating from Jiménez-

Crespo’s focus on localization as process and text as object, Schäler (2006, p. 3) advocates a broader, utopian conceptualization of localization as “the linguistic and cultural adaptation of a digital product or service to the requirements of a foreign market and the management of multilinguality across the global, digital information flow.”

To form a tight concept field for contextualizing localization, Cadieux and Esselink

(2002) propose a formulaic representation of the overall globalization environment with the redefined terms—GILT, where G stands for Globalization, the top term in this partitive concept system, meaning the adaptation of a thing to multiple markets; I for

Internationalization, which consists in all the preparatory work that facilitates the subsequent localization of the said thing; L for Localization, which is adapting a thing to the needs of a given market; and finally, T for Translation, a rendering from one language into another. In this hierarchical system, Translation is part of Localization, which, along with

Internationalization, constitute Globalization.

With the introduction of both localization and translation, it is necessary to briefly discuss the conceptual relationship between these two terms, since the current dissertation

intends to address website localization from the perspective of translation studies. In the industry environment of digital product development, translation is regarded as one component of localization process. This is largely due to the fact that localization requires a degree of technical adaptation that is relatively unknown to the isolated act of translating texts oftentimes for hardcopy production. For a comprehensive view of content creation within modern authoring and localization environment, Wright (2004, p. 589) introduces a technology-oriented workflow paradigm where the traditional sequential chain of document production is supplanted with an iterative and incremental process. This paradigmatic shift significantly alters the translator’s role in the product-related information lifecycle.

The technology-oriented localization workflow has brought about the emergence of new specializations and job profiles, such as localization translators, quality control specialists, software developers and engineers, each playing a part in a large team and adding to the dynamics of localization industry, taking in disciplines other than translation per se

(Tennent 2005, p. 103), Translation is thus becoming increasingly integrated into the broader document-production process (Bowker, 2002, p. 139).

If translation is part of localization as the abovementioned discussion indicates, this implies that, in the words of Sandrini (2005), the localization professional is in command whereas the translator merely acts as a contributor of foreign-language texts. Seen from the perspective of translation studies, however, the process of translation involves linguistic as well as cultural transfer and the communicative intention or function of the target text is of overall importance. Translation, therefore, always involves some form of adaptation with respect to the text itself or other items relevant to the document such as graphics, etc. After

all, translation, as a task, has a centuries-long history, whereas localization is a phenomenon

over the past 30 years—maybe just a new name, a specific type of translation. In this sense,

translation should then be viewed as a concept broader than localization.

Moreover, localization can also be viewed as part of translation when analyzed in

terms of texts only, as contended by Mazur (2009, p. 352). If localization is about adapting a

text so that it accounts for the local (i.e., target culture’s) linguistic and cultural norms and

conventions, then it seems that the idea is already well established in both translation studies

and practice. For a detailed discussion, see Nida’s dynamic equivalence (1977), Nord’s

instrumental translation (1991b), House’s covert translation (1977), or Venuti’s domestication

(1986). In all, the variation in approaching the relation between localization and translation is attributable to different standpoints.

While the differentiated conceptualization of localization and translation will remain a topic of debate in both industry and academia for some time to come, certain industry trends point towards the possible convergence of these two concepts. Sargent and Ray (2010, p. 2) observe that resource bundles make software strings easier to handle by standard translation tools and processes, somewhat eliminating the distinction between localization and translation. On the other hand, Esselink (2003a, p. 85), when examining the prospect of overall industry development, argues that where localization firms once distinguished themselves from traditional translation companies by specializing in translation, engineering and testing of software applications, now most of them are migrating to web localization solutions. Esselink further predicts the possible industry dynamics where localization industry will slowly be integrated back into translation industry to form the “multilingual

publishing industry” or “multilingual solutions industry” when large localization firms keep moving upstream and offering content creation and product support solutions.

On the whole, theoretical discussions about localization and translation have long

orbited around a rather predictable set of issues featuring prominently the role of technology,

automation, standards, interoperability, and efficiencies (Van Genabith, 2009). The reason for

this, as Schäler (2010, p. 213) sees it, is that the discussion about as well as the research on localization issues has been dominated by the pragmatic, commercial agenda of localization industry, an industry driven almost exclusively by the desire to maximize the short-term financial return on the investment of multinational digital publishers in developing digital content.

Therefore, to expand the industry-oriented focus characterizing current mainstream

localization activities, the dissertation conducts a textual-linguistic study to add to the prevailing technology-driven, industry-focused approaches that highlight dimensions other than the text and language. It is expected that the current study can augment the understanding of website localization from the perspective of translation studies.

Website localization, if approached from the standpoint of fulfilling the overall purpose of the localized product, can be defined as the process of modifying a website for a specific market according to the goals outlined by the client, in which the term “market”

refers to a group of people (a region, a country, or a language community) who share a

language, a writing system and other properties which may require a separate version of a

product (Yunker, 2002, p. 17). The specifics of website localization, as Pierini (2007) sees it,

“involves the translation of all pages, including all purely linguistic elements: lexis

(graphically separated blocks of writing), alternative texts, links, and support

documents. When needed, it also includes the adaptation of the source text to ensure

the acceptance and the success of the product in the local market: e.g., the adaptation

of dates, weights, measures and currencies; the modification of content, by omitting

information not relevant to target receivers, adding extra information, or practicing a

summary translation of the source text; a change in style, by employing the writing

style conventionally used in the target culture.”

Taking into account the difficulty in reaching a consensus about a time-tested definition of localization, “non-localized English websites” in the current study refers to the selected US-based organization websites in English language, while “localized English websites” refers to the selected China-based organizations’ English-language websites, both targeting the English-speaking market. From the aforementioned discussion, it can be seen that the term “Localization” has been known for its two key features, technology- and market-orientedness. However, considering the increasing level of technology integration in localization and translation process, it is almost impossible to distinguish localization from translation in terms of technology alone. Besides, when it comes to English-language digital products rendered from other languages, “target market” often becomes a problematic concept. In view of the challenges in developing definitions, the current study approaches website localization as an undertaking of bringing a Chinese-origin website into English culture and language, while highlighting the product-specific features related to language and text.

The problematics in website localization involves more than the consideration of

cultural differences and technological influences. The published studies in this field seem to

be dominated by prescriptive frameworks and evaluations, though a consensus has yet to be

reached over what “should” constitute a competent website. As Pym (2010, p. 12)

provocatively points out, the books that relate website communication to the theories of

cross-cultural marketing tend to emphasize the need for cultural adaptation, whereas the

tendencies found in websites have more to do with the creation of new, creative cultural

communities. It has been argued that localization, in keeping up with the fast pace at which

technology advances, has not fully benefited from translation-related theoretical concepts that

could help shape many localization processes in a more effective way, as is the case with the

notion of convention (Jiménez-Crespo 2009, p. 80). To boost the efforts at identifying the gap

between the academic theorization and the actual web ecosystem with real-world evidence, the dissertation underscores the autonomy of localization products by descriptively analyzing the conventions of selected English websites localized from simplified Chinese. In this

regard, acknowledging and appreciating the linkage between localization and translation

studies can offer a new research paradigm.

1.1.3 Charting the territory of website localization with the map of Translation

Studies.

As regards the conceptual discussions of how Localization and Translation Studies

interrelate and interact with each other, some strong voices have already arisen from

published literature. Jiménez-Crespo (2010, p. 287), having identified the localization

experts’ dated understanding of translation as an intellectual activity “focused on

communicating the meanings and messages of words” (Lommel, 2007, p. 7) or as “just a

language problem” (Brooks, 2000), points out that such simplistic conceptualizations

disregard essential communicative, pragmatic, functionalist, cognitive and sociolinguistic

aspects of modern translation theories and paradigms. According to Folaron (2006, p. 5),

throughout its disciplinary history, Translation Studies has critically engaged with issues

intimately linked to language, culture, and society and problematized social categories (race

and gender), concepts (power and ideology), and historical time periods (classical,

structuralism, and postmodernism). The disciplinary reading of translation and localization

technologies, as Folaron (ibid.) argues, can be enhanced by moving beyond the observation

or description of specific tools, procedures, and applications to inquire into the multiple,

complex dynamics currently shaping practices of global communication. To achieve such an

enhancement, translation studies can adopt and adapt the insights, models, and methodologies

organic to its history and expand its discursive space to include cross-cultural communication

through translation in a digital world mediated by technologies. Along the same line, this

dissertation directs the spotlight on the localized website, a digital product resulting from the

confluence of technologies (the computer and Internet) and translation.

Some general introductions to translation studies have already attempted to include

the area of web localization but with rather modest results (Sandrini, 2005, p. 3). Williams and Chesterman (2014) see the following research areas: "establish the current practice, investigate the effect of website constraints and user demands on translator's decisions both on the micro and macro level, evaluate the product, and explore the feasibility of using controlled languages into website design to facilitate translation." The current product-

focused study aims at achieving a broader understanding of localization by examining selected Chinese for-profit and nonprofit organizations’ websites targeting English-speaking visitors.

In his seminal book Translation and Web Localization (2013), Jiménez-Crespo presents a more comprehensive view of current and future development in the studies of web localization. The main research topics this book identifies and discusses are the reconceptualization of “text” in web localization, web-based genre analysis, quality of web localization, guidelines for conducting empirical research in this field, localization competence, and the impact of professionalization and crowdsourcing. Among them, genre analysis of textual-linguistic features is of special interest to the current study of localized websites.

1.2 The Research Topics under Study

Following the clarification of key terms and concepts underlying the dissertation in

Section 1.1, this section will highlight the main research topics to be addressed in the current study. On the one hand, the dissertation fills the literature gap on website localization by redressing the prevalence of some themes. On the other, it opens up new arenas of research by exploring the influence of industry and source language on the textual-linguistic features of localized websites.

1.2.1 Counteracting some current trends in the studies of website localization.

Two leading research trends in the published studies of website localization are identified to be reassessed by the current study. Firstly, extralinguistic concerns, especially visual design, are overemphasized at the expense of linguistic concerns. This is largely

attributable to the fact that the non-textual elements of websites are often highlighted to

differentiate this multimodal medium from other conventional media, such as print and

television. Secondly, the assessment of website localization is greatly influenced by the

industrywide maxim that localized texts should look “like (they have) been originally

developed in the target market” (LISA, 2003, p. 11; my addition in parentheses). In practice,

it means that localized websites are evaluated for their adherence to the conventions of the

target market or culture and any deviation is simply dismissed as localization mistakes or

failures. However, as previous studies have already proven, localized website texts do not

necessarily share the same set of conventions with texts originally produced in the target

market (Jiménez-Crespo, 2009).

1.2.1.1 Textual-linguistic concerns overshadowed by technological and extralinguistic ones.

As a lucrative, dynamic, and inter-professional field, website localization often

involves marketing, design, and software engineering, as well as linguistic processes (Pym,

2010, p. 1). According to Lako (2012, p. 358), the elements important for website localization

process can be classified into front end (“what the website visitor sees on the website interface”) and back end (“what goes behind the scenes”). Among them, navigation structure

and Content Management System (CMS) have never been dealt with in conventional text

translation. The former is a front-end element, represented by navigation menus and page

hierarchies, while the latter is a back-end element allowing control over the localized content

for real-time updates. As argued by Pym (2010, p. 1), the localization of a website differs

from non-hypertext translation with respect to the identification of translatable elements, their

non-linearity, the rendering tools needed, the way in which the translation process is prepared and coordinated, and the extent of the changes that may by introduced.

For all the disagreement between academia and industry over a most complete picture of website development and localization, both sides concur with the idea that the design of the webpage is at least as important as its linguistic content, which should be arranged in such a way as to accommodate screen reading. As Pym (ibid.) points out, unlike a printed page, a webpage should be built for use, not just for reading. However, the prevalent accentuation of design over content in scholarly writing seems to go so far as to overshadow the textual and the linguistic.

Most published studies of website localization can be found in the fields of

Information Systems (IS) and marketing, where anything but the website text is given close attention. A literature review (Chiou, 2010) shows that the former centers around technology- oriented factors, e.g., usability, accessibility, navigability, or information quality, while the latter mainly evaluates advertising, promotion, online transaction, order confirmation, or customer service. Both approaches underscore the extralinguistic dimensions of websites, which is understandable since form, far more than content, sets websites apart from conventional mass media.

However, color, design and functionality highlighted at the expense of language and text seems to be carried so far that it is not rare to read statements like “using local language in proper context and style is only a small part of the localization effort. Companies also need to consider adapting colors, icons, signs, web page layout, number format, date format, …”

(Singh, 2004, p. 3; italics added). Ironically, the same author does recognize the complex (yet

“insignificant”) language adaptation in website localization: “languages do not just differ in

terms of characters, syntax rules, and punctuation, they also differ in terms of their origin,

their emphasis on history and tradition, their use of dialects and rhetorical styles, their use of

symbols and metaphors, and even their use of persuasive strategies” (ibid.).

To add to the discussion of what text and language means to localization, Garcia explains the bearing a diminished view of the text along with the demotion of the translator’s role has on the issue of quality:

In localization, text is purely seen as a commodity, with little intrinsic value other

than its usability. Translators are perceived less as skilled artisans dealing with the

holistic properties of the text, than as assembly line workers who attend to the

controlled language-like traits of the segment …While in publishing, quality can be

to some extent implied by the artisan status of the translator and the stable properties

of the text, in localization it is just another aspect among many that needs to be

measured (2008, p. 51).

In fact, conventional textual-linguistic features are indispensable to online presence and “the text still remains a key information asset within a web page” (Sandrini, 2005, p. 2), although the presentational deviation of the web from conventional mass media is noteworthy in website evaluation. The major goal of website localization, like that of any localization initiative, is to expand the usability of a final product (a website in this case) to a broader set of users, for whom language and associated locale issues are defining elements of their customer experience (DePalma, 2012, p. 2). For Eisenberg (quoted in Singh, 2005, p. 23), the web has evolved through four phases: the technology phase (a focus on gopher and bulletin

boards), the design phase (a focus on designing attractive sites), the marketing phase (a time

of unfettered marketing spending with little concern for revenues and profits), and today, the

business phase, highlighting return on web investment. As the dust settles from the

mushrooming development of technological gadgets, it is time to reflect on text and language

to ensure well-directed, budget-friendly web success.

1.2.1.2 Creative and innovative deviations silenced by overhyped adherence to target-

market conventions.

In addition to the difficulty of balancing textual and non-textual considerations, the

website localizers are also faced with the dilemma of conformity and individuality in

promoting website effectiveness. Maintaining an effective website has become vital for a

business to strengthen its customer relationships and gain a larger market segment (Law &

Buhalis, 2010, p. 1). The eternal dilemma of advertising and marketing, in De Mooij’s view

(2004, p. 206), is whether to follow the conventions for a product category in the target

culture or to be distinctive to raise awareness and find a place in people's memories. The risk

of using distinctiveness to attract attention is that it will not fit in consumers' schemata and

thus be discarded. For instance, people of high-context culture who are used to symbols, signs, and indirect communication will process information in a different way than people of low-context cultures who are used to explanations, persuasive copy, and rhetoric (ibid.).

Therefore, marketers are most often hesitant to unleash the power of uniqueness by venturing out of consumers’ comfort zones.

Furthermore, culturally congruent websites have long been promoted in academic literature as the best practice since they can enhance website usability, which can induce

more favorable attitudes toward the site and ultimately increase business opportunities (Chun,

Singh, Sobh, & Benmanmoun, 2015; Vyncke & Brengman, 2010). Website visitors may recognize cultural congruency to various extents at different levels, including language, functions (site ergonomics, functionality, and technical speciﬁcations), and graphic designs

(typical cultural markers such as colors, national references, symbols, and heroes)

(Bartikowski, 2014). Of the three levels, website language receives the least attention in academic literature. In one study of localized websites (Singh & Kalliny, 2012), the proposed assessment framework features only one textual-linguistic variable, “translation quality,” with no further sub-divisions; the evaluators (two bilingual students) browsed through 50 webpages of each website under study and gave a score using a five-point Likert scale based on their overall impression.

There is not much difference between academia and industry this time in their approach to website development. The prevailing guidelines for website design and industry analyses of web conventions seem to make every effort at achieving universalism and generalization, with little regard for possible nation- or language-specific differences. This may be explained by the convergence theory (quoted in De Mooij, 2004, p. 51), which proposes that nations along with industrialization and modernization are becoming increasingly alike despite different cultural and historical legacies and diverse political economic systems.

However, as McLuhan (quoted in De Mooij, 2004, p. 255) contends, technological innovations are merely enhancements or extensions of humankind. They are generally used by people to enhance current activities; they do not change people's values or habits. As

technical expertise diminishes as a differentiator adding value, cultural expertise has increased as a source of revenue and as a unique selling point (Sargent & Ray, 2010, p. 2).

Hence, this dissertation attempts to add granularity to the textual-linguistic convention analysis of website localization and in turn to revise the common perception that localization is successful provided the origin of the material can no longer be detected. In an increasingly globalized society, publishers, marketers and advertisers play with “strangeness” and stereotypes (Schäler, 2006).

With an exploration of textual-linguistic features of selected organization websites, the next analysis deals with two major factors influencing the identified features of localized websites: industry (Section 1.2.2) and source language (Section 1.2.3).

1.2.2 Exploring Industry-specific influence on localized websites

The current study will conduct both within- and cross-sector analyses to identify the textual features of an organization website due to industry-specific influences. Decoding the differences among various industry sectors is important not only for industry analysts; as a result of the comparative study conducted in this dissertation, a clearer picture of industry sectors as represented by organization websites can lead to a better understanding of web- based writing styles followed by different trades and professions.

In addition to differences and deviations, the dissertation will also identify the textual- linguistic similarities shared by both localized and non-localized English websites from selected industry sectors, thus providing real-world references for translators and writers of web content (see Chapter 3 for research methodology).

Serving as a starting point, the dissertation will study a sample of organizations from

five selected industry sectors — educational institutions, governments, tourism destinations, e-commerce and translation companies. In the near future, further work is expected to be done for many more industry sectors as the industrial world embraces greater variegation.

Sargent and Hegde (2012) give the following explanation for the diversification of industry

sectors:

As countries advanced along the trajectory from resources to information, a diversity

of industrial sectors naturally occurs among the prominent, native companies. That’s

because, while existing businesses in older industries may consolidate, the need for

resource, manufacturing, and service companies does not disappear. Meanwhile, new

companies are forming at the next stage of economic advancement – such as services

or information – creating ever greater diversity within the economic base for that

country (p. 25).

1.2.3 Searching for a variant of written English in web-mediated organization

discourse: Source language-specific influence on localized websites

In general, organization websites in multilingual versions arise from the increasing

needs for international business and communication as well as the development of web

technology. Pym (2009, p. 139) describes a hierarchy of languages in localization industry

and the resultant directionality as follows:

Some [languages; added by the author] are central and used for production, others are

semi-central and impose strong constraints on consumption, and still others are

virtually excluded from the relations of production, consumption, and translation.

Within this hierarchy, translation tends to move from centralized production to

semicentral consumption. This often means going from English to all the major

languages of the world. Localization is thus marked by a strong directionality, moving

from the central languages toward the more peripheral languages. So strong is this

directionality that movements in the other direction have been called “reverse

localization” (Schäler, 2006) … As economic globalization increases, we might

expect the phenomenon of reverse localization to become more important.

The current study of selected websites localized from simplified Chinese into English

does not only respond to the growth of reverse localization as defined in the above quote, but

also strives to reveal another sense of reverse localization, which is “keeping or intentionally

introducing linguistic or cultural strangeness into digital content for a particular target market with the aim of intentionally differentiating a digital product or service from the dominating culture in that market” (Schäler, 2006, p. 12). Even if the ultimate goal of localization is releasing localized texts that are received as locally-made products (LISA, 2003, p. 5), it has been observed that distinctive constraints during the localization process lead to target texts with distinctive linguistic features (Jiménez-Crespo, 2009, p. 97). Besides, it is believed that strangeness can work towards commercial success, not by adapting digital content to the culture and the language of the target country but by doing exactly the opposite to develop a possibly most attractive selling point (Schäler, 2006, p. 11). Therefore, the practitioners of website localization are both challenged and inspired by what should be adapted to the host culture and what should be kept “strange.”

If it is advisable for the host culture to embrace some new yet deviant inputs from the

source culture in website localization, we can see no reason why the host language cannot do

likewise to benefit from the marketing charm of strangeness. Some scholars have long

advocated for the acknowledgement of World Englishes, English as Lingua Franca (ELF), or

Global Englishes, arguing that English used and developed in countries other than native

English-speaking ones should not be simply dismissed as misused or faulty English, but be

viewed as different variants of English to promote international and intercultural

communication (For the most recent review of relevant literature, see Jenkins, 2015). As

such, the Englishes localized from different source languages can also be viewed in this

positive light to enrich rather than baffle web-mediated communication (see Chapter 3 for

further details about the published studies of English-language websites localized from simplified Chinese).

By informing localization training and practice of empirical evidence, the descriptive, product-oriented case studies characterizing the dissertation resonate with the “pragmatic turn” of Translation Studies (Wilss, 1987; quoted in Snell-Hornby, 1988, p. 67) in that the

disciplinary field has gained impetus with the rise of sociolinguistics and cross-cultural studies, which view language in its infinite variability and in relation to culture and communication.

1.3 Summary

Beginning with an introduction to the key terms and concepts underlying the dissertation (Section 1.1), this chapter briefly pinpointed how the current study of website localization would address some of the gaps and inadequacies identified in the existing body

of relevant knowledge. Specifically, approaching localization from the perspective of translation studies will put a spotlight on the “traditional” textual-linguistic aspects seldom attended to in previous technology-focused studies (Section 1.2.1.1). In addition, refocusing on the textual-linguistic dimensions of website localization will counteract the overemphasis of extralinguistic concerns (e.g., color and design) prevailing the published studies. Secondly, conducting descriptive and comparative analyses of localized and non-localized websites will test the prevailing prescriptive guidelines and evaluations of web design and content writing with empirical evidence., so as to show that the identified features of localized websites actually highlight rather than eliminate strangeness for marketing success (Section 1.2.1.2).

Thirdly, the comparative study will explore the industry-specific influences on the textual convention of an organization website by analyzing website texts from selected industry sectors (Section 1.2.2). Lastly, the current study of English websites localized from simplified

Chinese will explore the existence of one or a few variants of written English, thus adding to the dynamics of Global Englishes and enriching the understanding of ELF by reflecting in a positive light upon the influence of localization and translation on the receiving market and culture (Section 1.2.3).

Following the general introduction in Chapter 1, the next chapter will delimit the scope of the current study by specifying the research questions to be answered by the dissertation, accompanied by a literature review for each research topic the dissertation deals with. Chapter 2 will also briefly discuss the research questions thus formulated as well as the assumed answers for them.

II. Scope and Significance

Built upon the theorization of Chapter I, this chapter specifies the scope of the dissertation by clarifying the research questions and corresponding basic assumptions, and then explains the significance of the current study. In the end, the structure of the dissertation is devised before a summary of the current chapter.

As a commercially dominant modality of localization, website localization has flourished as a reaction to the ever-expanding need for more web-based localization environments (Bahri & Mahadi, 2015, p. 33). Website texts, like any other text on the web, are generally influenced by and in turn influence the communication dynamics of the

Internet, which can be considered as a tool of cultural transformation in its own right.

However, national or language-specific differences are not completely eliminated and should be considered (ECDGT, 2009, p. 29). As discussed in 1.2.1, previous studies tend to investigate the themes and designs of corporate websites employing the theories of IS, marketing, or corporate communication. On the other hand, the linguistic exploration of organizational discourse for online communication is not yet adequate, especially from

China’s perspective. Moreover, there is very little research looking at organization websites from a quantitative, linguistic, and analytical perspective in the context of website localization (Shan & Wang, 2017, p. 1171). This worldwide “lack of

interest in linguistic issues” (Gâţă & Praisler, 2015, p. 129), also shared by website

administrators and/or designers, may find partial explanation in the non-translation strategy

prevalent in promotional localization, such as the localization of the same advertisement to be

launched in different countries (Rodríguez, 2016, p. 135). In promotional translation, most or

even all of the original text is usually left untranslated, oftentimes to retain the symbolic

value of the source language and culture. However, translating promotional materials

including advertisement is not only about communicating product values, but also about

communicating the values of the brand and the values of a culture, or providing information

about the price, the usage or the services offered (Rodríguez, 2016, p. 140). Textual content

makes a significant contribution to presenting these communicational aspects and translation

plays a fundamental role in transmitting relevant values of brand and culture, manipulating

textual material if needed, in order to fully communicate the essence of marketing campaigns

(ibid.).

The academic field of Translation Studies to some extent shares the localization industry’s obliviousness to language and text issues in studying localized websites. The translation of website texts receives little discussion in the translation studies literature, although it has been recognized as involving problems and decisions on a few different translation levels, including cultural adaptation, information sequencing of hypertext segments and language use (Nauert, 2007, p. 1).

Only a few studies of localized websites published in English share a textual-

linguistic focus with the dissertation, among which Umoh’s study (2015) of oil and

gas company websites conducts a comprehensive literature review of studies on

localized websites and carries out a multi-dimensional analysis, including a sketchy examination of how much of the website is translated into the target language. In addition, Jiménez-Crespo’s comparative studies of localized and non-localized Spanish websites (2012, 2011a, 2011b, 2010, 2009, & 2008) mostly follow a methodological framework which is adopted and adapted by the dissertation. Based on these key references in addition to other published studies producing general hypotheses and analyses for further testing, the dissertation formulates four research questions and makes corresponding basic assumptions in Section 2.1 and 2.2.

2.1 Research Questions and Basic Assumptions

Digital texts have been identified as one of the main vehicles whereby conventions are transmitted from the dominant English language around the world (House, 2001). On the other hand, the emergence and development of “reverse localization” (see Section 1.4 for the definition and discussion of the term) shows that the increasing production and use of digital texts by different linguistic discourse communities may have led to the emergence of distinctive conventions (Jiménez-Crespo, 2009, p. 80). Therefore, to explore the possibility of existence of this trend in the websites of China-headquartered organizations that have been localized into English, this dissertation will study the conventional features of website texts by first of all answering a question about the most conventional components (refer to Chapter

3 for the specifics of research methodology):

2.1.1 To what extent are navigational terms and phrases standardized in the

selected localized websites under study?

According to Price and Price (2002, p. 45; quoted in Jiménez-Crespo, 2009), website text can be classified into interface text and content text. Jiménez-Crespo (2013, p. 32) defines these two types of texts as follows:

Interface text is all textual interactive segments that help tie the website together and

that provide the global coherence and cohesion to the hypertext and website, such as

navigation menus, dialog boxes, or controls in a chat. These segments are similar in

different websites belonging to the same genre and include, for example, the option to

profile picture. In contrast, content text can be defined as the specific text that makes

each webpage a hypertextual unit.

Sharing Jiménez-Crespo’s focus on interactive segments in most of his published empirical studies of localized websites, the current study, to answer this first research question, specifically examines the navigational texts within the category of interface text, including the texts presented in menus, buttons, and/or links that fulfill navigational purposes.

These navigational sections have been viewed as an area involving the most conventional texts on websites (Nielsen & Tahir, 2002). The attempt at exploring the textual convention of this area can help decide if the source-text (Chinese) convention has been replaced by the target-text (English) convention in localization. The assumption made here is that Chinese- language convention has been retained to some extent in the localized English-language

websites, though most navigational lexical units have shown consistency with their

counterparts in the non-localized English-language organization websites.

Moving from the most conventional to the supposedly less conventional texts, the next primary research question investigates the textual-linguistic features of the localized websites that can be influenced mainly by the source language of Chinese, apart from other potential factors, such as the presentational context of the web, and the technology-facilitated localization process.

2.1.2 To what extent do the localized website texts embody language-specific features?

The localization of the written content is important for due transfer of aspects such as dates, currencies, and units of measurement as well as for conveying the correct image (Bahri

& Mahadi, 2015, p. 36). In the dissertation, the content texts in different communicative sections of localized English websites will be compared against those of their comparable non-localized counterparts and their original Chinese versions to identify the conventional features derived from the target language of English or the source language of Chinese.

When reviewing the published literature, we can find that despite a wealth of studies comparing original and translated English for different source languages (including Chinese) and text types, to date there are few, if any, English-language publications that deal specifically with websites localized from Chinese into English. And most comparisons approaching localized and non-localized English websites with the source language of

Chinese from a textual-linguistic perspective are prescriptive error-based analyses for the main purpose of translation quality assessment (see Chapter 3 for an overview of relevant

comparative studies). As a key point of departure, the current study relies on a descriptive

textual analysis to contribute to the body of knowledge concerning the English-language

website conventions of organizations and institutions headquartered in China. The

assumption made for the current research question is that the influence of source language

(Chinese for the current study) is identifiable in the localized content texts under study,

though determining the extent of such an influence calls for further research.

So, if localization context and source language are left aside, what else can

differentiate localized English-language websites from their non-localized counterparts? The

next research question delves into the existence of industry influence.

2.1.3 Is there any industry-specific conventional feature of localized websites that

differentiates themselves from their counterparts from a different industry?

With the rapid development of economic globalization, projecting a positive image overseas and developing world-known brands have become vital for China-headquartered organizations, commercial or nonprofit, to enhance industrial and national core competencies and to implement the "Going Global" strategy put forward by the Chinese government.

Chinese organizations and institutions thus attach importance to establishing and maintaining their websites to achieve convenience, autonomy and interactivity while addressing cross- cultural challenges (Shan & Wang, 2017, p. 1170).

Most previous studies of localized organization websites concentrate on commercial

companies within one industry, or ecommerce in particular. Commercial websites, according

to Sierro Fernández’s observation (2016, p. 83), usually require fewer adaptations than other

types of websites, given that they contain few culturally-related elements. In reality, however,

website adaptation, or rather website localization, is no less important for businesses and

companies to reach target clients with a good understanding of their needs and due

localization will show prospective customers that the company understands and respects their

language and culture (Bahri & Mahadi, 2015, p. 35). The only recent English-language

academic publication approaching Chinese company websites localized into English from a

textual-linguistic perspective is Shan and Wang’s (2017) study of brand personality embodied in Chinese energy company websites. The dissertation will adopt and adapt the methodological framework proposed by this study to explore the industry influence on the organization websites from five selected industries: language industry, ecommerce, higher education, government and tourism destination (see Chapter 3 for selection criteria and sampling strategy). Both within- and cross-industry comparison will be conducted to answer the current research question and the assumption made for now is that there exist certain industry-specific features shared by localized and non-localized websites within the same industry, but the influence of these industry-related features can only become indefinite over time with the continuous blurring and shifting of inter-industry boundaries.

In addition to differences and deviations, the dissertation will also identify the textual-linguistic similarities shared by both localized and non-localized English websites from selected industry sectors, thus adding to the repository of empirical studies that inform the practice of translating and writing for the web in English (see the subsequent chapters for further analysis and discussion). For a further reflection upon all the findings gathered from answering the abovementioned three research questions, the next and last summative question

of the dissertation explores the possibility of existence of a written English variant in

localized websites.

2.1.4 Does a variant of English exist in websites localized from Chinese?

A wealth of convincing discussions has revolved around the overpowering influence

of English as a language of globalization, international communication, sciences, and

entertainment industry (Zafiu, 2010, p. 16). Widely defined within critical theories of

globalization, global English indicates the spread and use of English as a means for the

intensification of transnational social, economic, cultural and political relations, e.g., in global English media, information technology, and international specialized languages

(Russo, 2012, p. 9). Research on English as a global language has variously demonstrated how the specificity and difference of English language varieties is often not preserved in both interlingual and intralingual translation giving way to the homogenization or standardization of a global code, yet it may be useful to redirect present research by focusing on the translocal and transcultural aspects of global English and more specifically on the ways in which English language varieties and other languages flow and thereby influence global

English (Pennycook, 2007). Furthermore, it is believed that the center of gravity of English

will shift, with the old native English models of the US and UK giving way to a polycentric

heavily Asian-influenced English (Pennycook, 2007, p. 110).

An English website of a China-based organization, like its counterpart of any other non-English speaking countries, is confronted with the difficulty of identifying the target reader for their English websites (see Limon’s analysis of the Slovene website; 2008, p. 3). It is unlikely to target native speakers of English alone (who are likely to represent only a small

percentage of those accessing the site) – the target audience is probably everyone who does

not read Chinese, many of them very likely to carry out business communication with

Chinese organizations in English on a regular basis. Generally speaking, contemporary

English should be viewed as a medium of cross-cultural communication mostly among non- native speakers, sometimes between non-native and native speakers, and occasionally among native speakers. It has been argued that English in relation to China is at a stage of development much earlier than to those Outer Circle countries, such as India and Singapore (see Kachru’s three

circles of English; 1992). And because it is not developing by means of communication

among Chinese users of English, it is unlikely ever to be considered a variety of English in

the conventional sense of the term (Jenkins, 2015, p. 161). The tentative assumption made

here is that the emergence of certain features can be identified that deviate English used in the

localized websites from that used in non-localized websites.

After framing all four research questions and making matching assumptions in

Section 2.1, the dissertation then makes a subsection-wise assessment in Section 2.2 of the

significance of the current study in the exact same order as the four research questions are

presented in Section 2.1.

2.2 Significance of the Current Study

Ultimately, the comparative textual-linguistic analysis underlying the current study of

localized English texts aims at empirically substantiating the declaration that with the

widespread use and adaptation of English, non-native users can be accorded at least the same

English language rights as those claimed by mother tongue speakers, including the right as

follows:

...... [T]o innovate without every difference from a standard native variety of English

automatically labelled “wrong.” This is what it means for a language to be

international - that it spreads and becomes a global lingua franca for the benefit of all,

rather than being distributed to facilitate communication with the natives (Jenkins,

2015, p. 53).

The main question with innovations is the need to decide when an observed feature of language use is indeed an innovation and when it is simply an error. An innovation is seen as an acceptable variant, while an error is simply a mistake, or uneducated usage. If innovations are seen as errors, a non-native variety can never receive any recognition (Bamgbose, 1998, p. 22).

Moreover, just because a language item differs from the way it is produced by Inner

Circle speakers such as American and British speakers, it cannot be assumed to be an error but may be an example of contingent creativity and adaptation, or even of language contact and change in progress (Jenkins, 2015, p. 41). Therefore, it is concluded that what would be considered deficient English, in the global context, “may be a matter of difference which is based on vital sociolinguistic realities of identity, creativity and linguistic and cultural contact” (Bolton & Kachru, 2006, p. 11). The dissertation thus analyzes the linguistic features of localized English for an exploration of a possible English variant most likely produced by non-native users and not necessarily inferior to native English.

Specifically, for the purpose of the current study, each of the subsections under

Section 2.2 corresponds to its counterpart under Section 2.1, further clarifying the significance of addressing those separate yet related research topics of the current study.

2.2.1 Providing language- and culture-specific references for localization practice and evaluation.

A majority of previous academic studies on website localization has displayed a growing tendency to stress the extralinguistic aspects of localization, which differentiate

localization itself from the conventional sense of translation handling “monomodal” texts.

Language and text are thus often regarded as “superficial cultural differences” (Purwaningsih,

2015, p. 3). Since the word “culture” is inclined to cover a scope wider than the linguistic

issue alone, i.e., converting the text into the target language (Bahri & Mahadi, 2015, p. 34),

issues involving language and text tend to be marginalized due to the familiarity of

Translation Studies academia with this aspect in all the other more established branches of

knowledge. To underscore the new dimensions introduced to translation by localization,

O’Hagan and Ashworth (2002, pp. 66-78) consider localization as the “culturalization” of the

message. And the translation of business messages, such as product or brand names, as Bahri

and Mahadi (2015, p. 36) argue, calls for the expertise in commercial fields including

international market research and multicultural advertising. And these commercial fields

normally provide advice on very diverse issues rather than “immediate translation problems”

(O’Hagan & Ashworth, 2002, p. 73).

In an effort to counteract the trend of language and text overshadowed by technology

and process, Torres del Rey and Rodríguez Vázquez (2017, p. 3) criticize the prevalent

marginalization of language and text issues in the studies of localization as follows:

Typical approaches to localisation from non-translation-oriented spheres in the

industry (or in the public opinion) tend to consider the work of a localiser, from a

linguistic point of view, a question of literally substituting text strings in one language

into another, a 'simple' matter of finding the right equivalent. These views fail to take

into account the basic principles of communication and language in action, for a

specific purpose: among others, (i) the paramount importance of the context —the

place, time, participants, circumstances and shared knowledge surrounding the

production and reception or use of language, i.e., the situational context; the texts and

signs that accompany the language we want to communicate, with which they co-

construct meaning, i.e. the co-text; and (ii) the pivotal role of expectations and

conventions in the way people approach and process every text genre and, in general,

every means and medium of communication and interaction, without excessive

cognitive load or the help of external, complementary resources. Both key aspects—

context and conventions—can vary greatly from one language and culture to another.

In most cases it is the lack of appropriate linguistic and cultural input that makes a website localization project less effective (Bahri & Mahadi, 2015, p. 35). Therefore, the textual convention should be an essential concern for practitioners, evaluators, and trainers dealing with any type of localization and website localization is no exception. According to

Schäler (2006), while the technical problems of localizing the digital content on the web have been solved in principle if not strategically, the question of how to adapt this content culturally has not yet been answered. As the first research topic the dissertation addresses, the convention analysis of the most conventionalized website text, the navigational text, serves as a starting point for promoting a better understanding of organization websites in localization.

2.2.2 Decoding the language of localized websites: An undertaking to enrich the

studies of applied Internet linguistics.

The Internet is a field dependent on language (Crystal, 2011, p. 92), written or spoken, and even in cases of websites consisting of no more than images on screen, language is present in the underlying content specification of the pages, as part of the metadata. The language features or facets of the Internet, “facet” being a term adapted by Herring (2007) from the field of knowledge management, are classified into technological facets and social facets. These two categories are defined as follows:

Technological facets characterize the medium, determined by the associated computer

hardware and software and by the character of the protocols governing the various

outputs. Social facets characterize the number, relationship, and behavior of those

using the medium, the content and purpose of their communication, and the language

they use.

As a type of the social facets characterizing the website, language conventions,1 or the linguistic conventions recognized by participants in this type of online organization communication, is the focus of the current dissertation. It is the author’s expectation that the

current textual-linguistic study of organization websites in localized and non-localized

English can add to the applied branch of Internet linguistics. The leading advocate of such an

emerging disciplinary field, Crystal (2011, p. 2), defines Internet linguistics as a scientific

study of all manifestations of language in the electronic medium. Applied Internet linguistics,

1 In Herring’s conception (2007), the actual wording of the term is “norms of language.” However, from the perspective of Translation Studies (Nord, 1991a), norms are binding, and their violation usually arouses disapproval of some kind among the community concerned. whereas conventions are not binding, they embody only preferences. For the purpose of aligning with descriptive translation studies, the current exploratory study uses the term “language conventions” instead. 36

as Crystal proposes (2011, p. 3), aims at providing solutions to the problems of language

management encountered by various Internet users, in search, e-advertising, and online

security. Following the research approach upheld by Crystal (ibid.), the current study strives

to strike a balance between the description of formal properties of Internet language and the

study of the underlying communicative purposes and effects.

According to Crystal (2001), the emphasis in global communication through the

Internet has slowly shifted from technology to people and purposes. And as the Internet is

increasingly viewed from a social perspective, so language as a social phenomenon takes

center stage. Within this context, the linguistic focus characterizing the current study of

English-language websites can be expected to facilitate the empirical exploration of the most prevalent type of Internet output (Internet output is defined as one of the various entities which form Internet discourse, such as websites, emails, and blogs; see Crystal, 2011, p. 10).

The convention analysis of selected website texts for the second research topic of the current study investigates the textual content on the webpages that is presumably less conventional

than navigational texts, to allow for a firmer grasp of textual conventions in localized and

non-localized English-language websites.

2.2.3 Addressing business, economic, and social concerns: Language planning

and management.

If we somewhat adapt Crystal’s (2011, p. 1) conception of a linguist’s job, we can say that an Internet linguist’s job is to seek out, describe, and analyze manifestation of language over the Internet. Part of the task of an applied Internet linguist, similar to that of any applied linguist, is to identify, categorize, and share the linguistic practices in the Internet community

with the hope that the amount of observations could sensitize the legal instances to the necessity of a regulatory organ or institution for the web-mediated communication. And local practices may be improved based on protocols of communication and counselling with specialist linguists and translators in order to avoid neglecting basic communication principles such as observing linguistic regulations in use (Gâţă & Praisler, 2015, p. 150). On the whole, language planning and management is necessary on a theoretical and practical basis in the present-day context of international companies acting on local levels, as shown by Neustupný and Nekvapil (2003) and Nekvapil and Sherman (2009).

Of all the Internet users, organizations should be the ones most interested in language planning and management for websites, since it is in their best business, economic, or social interests that their websites can effectively reach the public, including stakeholders and/or potential customers. Most published studies of organization websites are focused on commercial organizations for attracting business interest. In the current era of globalization, a lot of companies are expanding their business into new markets, most of them having a website where they promote and sell their products and services. This fact implies that they need to localize their websites in order to reach global audiences (Sierro Fernández, 2016, p.

84). A literature review of relevant studies conducted by Bahri (2015, p. 34) highlights that localized web content increases usability, access, and website interactivity, thus leading to more web traffic and business activity on the web.

In commercial practice, simshipping, defined as an enterprise activity for releasing all language versions of a product simultaneously (Ressin, Abdelnour-Nocera, & Smith, 2011, p.

320), is rare for the websites of organizations, which tend to launch one language version,

most often English, before further localization into other language versions. This may reflect

the lack of guidance in evaluating current localization efforts and in suggesting areas for

improvement (Chao, Singh, & Chen, 2012). In addition to which language version(s) to

launch first, the localization industry also needs to consider how well a localized website

fulfills the purpose of reaching the target public, so as to make a proper measurement of

Return on Investment (ROI). Therefore, the dissertation will perform a real-world analysis to inform website localization targeting English-speaking markets.

Fully aware of the significance of online corporate communication, Chinese companies have already been investing considerable resources in building their English website. If these websites are simply translated from Chinese and fail to communicate appropriate identify and personality of brands, these expenditures may be wasted, or even counterproductive (Shan & Wang, 2017, p. 1178). A strong and favorable brand personality can help build positive brand associations, and reinforce brand identity, which can sustain companies’ unique competitive advantages, improve customer satisfaction and loyalty, influence their buying decision, and then increase companies’ turnover, profits, market capitalization and stakeholder value (ibid.). The dissertation, by comparing the localized

English websites of selected Chinese organizations with their non-localized counterparts of comparable US-based organizations, will propose some managerial best practices for effectively managing the brand personality dimensions embodied in English website texts to develop a unique organization identity in the international arena.

One topic of interest in studying organization websites is industry influence. A previous study (Singh, Zhao, & Hu, 2005, p. 141) comparing the cultural dimensions of

Chinese and American electronics and automotive company websites shows that the main

industry effect seemed not all that signiﬁcant, but the researchers also suggest that the future

expansion of their study to other industry segments should reveal industry-wise differences in

the depiction of cultural values. Following this line of thought, the current study is focused on

five industries, language, ecommerce, higher education, government, and tourism, for a broader view of industry-specific influence on the textual expression of localized English- language websites (see Chapter 3 for the criteria of industry selection).

2.2.4 Pedagogical implications.

The findings of localized and non-localized English-language websites (see Chapter 4

for details) can also augment the teaching and learning of localization. The definition of

localization as a translation-oriented and technology-intensive discipline (Torres del Rey &

Rodríguez, 2017) means that while translation does not necessarily deal with digital material,

localisation always takes place digitally, hence the need for higher digital literacy (Schäler,

2008).

In a digital world, specialized or expert professionals, challenged by the emerging

trends of democraticized translation activities such as crowdsourcing, fan translation, and big

data-related efforts towards the generation of automatic translation, are more than ever

needed to manage, process and perform quality control on the massive amount of data, and to

carry out the processes of transformation involving communication across languages and

cultures (Pym, 2000). Localization practitioners need guidance to localize corporate websites

culturally as well as linguistically (Shan & Wang, 2017, p. 1170) and also to become a

specialist in the industry and culture of the target texts (Bahri & Mahadi, 2015, p. 35). The

current textual and industry analysis of selected website texts can therefore facilitate

informed localization training.

Aside from providing empirical support for localization trainers and trainees, the

current study can also contextualize localization training in real-life setting. In localization

practice, all the chunks of website texts tend to be treated equally because of the electronic

tools designed precisely to separate text from context, thus leaving translators blindfolded to

the whole communication dynamics (Pym, 2010, p. 6). Figure 1 shows that the extracted

original text and its translation are aligned in paired sentences to facilitate sentence-by-

sentence processing in the Editor window of a widely-used CAT (Computer-Assisted

Translation) tool. In most cases, translators are expected to produce the translated texts (the right column) based on the decontextualized original texts (the left column), no original webpages provided as reference due to proprietary concerns or time constraints.

Figure 1. Editor Window of a CAT Tool, SDL Trados Studio 2014

In general, websites are seldom considered an object of translation. The translator is rarely involved in the overall process, thus translating decontextualized text materials. And

web design decisions, implying cultural background knowledge, are often left to advertising

companies (Nauert, 2007, p. 3).

In this sense, the current descriptive convention analysis of localized websites can

produce contextualized teaching materials to better prepare students for the decontextualized

professional environment. As suggested by Pym (2003), translator training should be

relatively context-bound and example-oriented. Students need help to create and work with their own dynamic strategies in authentic translation situations rich in the complexity of real- life language mediation tasks (Kiraly, 2000). Therefore, the empirical evidence provided by a descriptive textual-linguistic analysis as the current study presents is essential for both

localization and translation practitioners to acquire a better understanding of web-based

textual conventions.

Turning attention from practice and industry to the pedagogic world of localization,

we find that due to the scarcity of empirical studies on localization and localization

competence (Jiménez-Crespo & Tercedor, 2011, p. 999), the lack of delimitation with respect

to localization competence and its relationship to translation competence has meant that

localization training tends to concentrate on the acquisition of instrumental competences

(PACTE, 2005). This instrumental competence alone can account for the industry training

approach, more focused on the achievement of technology-related competences, separated

from the bilingual, extratextual and translation knowledge competences (Jiménez-Crespo &

Tercedor, 2011, p. 1000). Examples of instrumental competence include knowledge of CAT

and localization tools, document formats, and addressing encoding issues (Jiménez-Crespo &

Tercedor, 2011, p. 1018).

The overemphasis of instrumental competence in localization training can also be

attributed to the understanding that functional aspects of localized texts can be more

objectively assessed and identified than linguistic or pragmatic issues (Dunne, 2006). To

counterbalance the current trend in teaching and learning of localization, the dissertation

focuses mostly on the analysis of textual, pragmatic discursive and communicative aspects

that need to be tackled and that are often assumed to be acquired by translation trainees prior

to engaging in localization training (Jiménez-Crespo & Tercedor, 2011, p. 1001). These are mostly related to bilingual, extratextual and translation knowledge competences in the

PACTE (2005) model.

2.3 The Structure of the Dissertation

This dissertation comprises six chapters. As an overall introduction, Chapter 1 gives the essential background on the current study, defines relevant key terms and concepts, and presents the research topics addressed. Chapter 2 delimits the scope of the research in question by briefly discussing the specific research questions and formulating the corresponding hypotheses. The significance of the dissertation research is also included in this chapter, along with this overview of dissertation structure. Chapter 3 introduces the empirical research approach and descriptive research methodology underlying the dissertation, followed by a procedural description of the collection and compilation of research data as well as a presentation of the analytical framework adopted. Chapter 4 presents the analysis findings of the localized and non-localized English-language organization websites under investigation and addresses the research questions of the current study. The last chapter, Chapter 5, summarizes the major findings before delving into

identifying emerging themes and issues, while drawing specific implications and

recommendations for language management and training in the translation/localization of

organization websites and discussing the limitations of the study and potential future avenues

of investigation.

2.4 Summary

In this chapter, the researcher reviewed the pertinent literature for each research question outlined to identify the gaps to be addressed in the current study, thus clarifying the scope of the dissertation research. From Chapter 3 onwards, the dissertation will mainly conduct a comparative textual-linguistic analysis of localized English-language websites for

Chinese organizations and non-localized English-language websites for comparable

American organizations. The analysis will specifically deal with four aspects: navigational texts, website body texts in different communicative sections, the possibility of existence of industry-specific influences on the textual expression of organization websites, and ultimately the possibility of existence of an English variant influenced by localization from the source language of Chinese. In the meantime, the significance of addressing each corresponding research question was explained in this chapter, touching upon such fields as textual linguistics, stylistics, discourse analysis of online organization communication, and sociolinguistics.

Based upon the general picture drawn by Chapter 1 and 2, the next chapter will delve into the details and explain the research approach and methods taken. Text sampling, data collection process, and analytical framework to be applied for the current study will be

described and data credibility, validity, and reliability discussed. A cross-comparison of the website data collected from different industries will be performed to ensure validity.

III. Research Approach and Methodology

Following the contextualization of the current study within the discipline of Web-

mediated organizational discourse analysis in Chapter 2, this chapter will describe the

research approach and the methodological framework adopted by the current study. The

conceptual difference between approach and methodology, as Hohmann (2014) sees it, is that

approach can be regarded as a focused way to deal with a situation or a problem, while the

proper methodology helps put approach into practice by providing methods and tools.

In regard to overall approach, the current research combines qualitative and

quantitative analysis by following the conceptual framework that originated from corpus-

based Descriptive Translation Studies. The aim of corpus-based translation studies, as affirmed by Olohan (2004, p. 17), should not be vague generalization based on quantitative data alone, but a combination of quantitative and qualitative analysis to explore the pragmatic factors related to discourse, genres and text designs. Qualitative research is inductive, that is, the theory is derived from research results, and qualitative analysis is often used in preliminary studies in order to evaluate the research area. By contrast, quantitative research is deductive in that hypotheses derived from the theory are proved or disproved during empirical investigation. According to Rasinger’s conceptualization (2013), quantitative analysis, oftentimes referring to the analysis of texts, patterns, and qualities in the field of

linguistics, is most commonly found in discourse analytic research, which fits the profile of the current study.

So far as methodology is concerned, the dissertation is characterized by an introductory implementation of a multi-dimensional comparison framework for performing statistical analysis of English-language website texts. This can be regarded as an application of dialectical thinking: qualitative analysis facilitates the understanding of a large quantity of data by providing categories for data classification, while quantitative analysis produces a mathematically sound result which often acts as a starting point for further interpretation within the initial framework. The framework is then usually refined over the course of several cycles, alternating between qualitative and quantitative research, until the acquisition of a thorough understanding of the data under study. During this process, qualitative analysis requires the analyst to deeply engage with the data beyond a mere description of what is happening that is facilitated by quantitative analysis. It is expected that the analytical framework under discussion will see continual refinement and development in future studies.

In actual practice, to achieve a balance between qualitative and quantitative thinking, the current study consists of two phases: the inductive Phase 1 and the deductive Phase 2.

Implemented in two steps, Phase 1 features a mainly qualitative analysis based on paired comparisons of Chinese and American organization websites both within and across industry, complemented by descriptive statistical measurements. The hypotheses developed in the paired comparison at Step 1 were in turn tested at Step 2, where grouped comparisons help decide to what extent the findings from Step 1 can apply to a larger sample of localized and non-localized websites. Some of the quantifiable features identified from the case studies in

Phase 1 were then revisited in Phase 2, where inferential statistical tests were run on a further expanded dataset of localized and non-localized websites. Such an eclectic approach to textual analysis, as Cristafulli (2014) proposes, should:

[H]armonize quantitative and qualitative types of research. Quantitative, corpus-

based research, which is typical of descriptive-empiricist approaches, yields

tendencies or regularities of translation behavior (whether historically determined

or universal). Qualitative analysis, on the other hand, is based on a critical-

interpretative approach to the textual evidence. It attempts to link the translator's

interventions with the coeval historical context, and aims at revealing the

individual translator's politico-ideological outlook (p. 37).

Figure 2 shows the logic relationship between Phase 1 and 2. Phase 1 began with a paired comparison of the leading Chinese and American organizations from the same industry sector, and the results of the paired comparison at Step 1 were then cross-validated with those of grouped comparison at Step 2, each group consisting of multiple organizations from a certain industry sector (see Section 4.3 for the calculation of required sample size). Only the industry sectors where both the Chinese and American organization websites have comparable section(s) were chosen for statistical analysis in Phase 2. A website section is a constituent part to help visitors navigate through the website, e.g., About us and Contact us (Bell, 2012). It is reasonable to assume that not all the selected organization websites necessarily have comparable sections, so it can be expected that Phase 2 will address fewer website sections and industry sectors than Phase 1.

Phase 1 (Step 1) Phase48 1 (Step 2) Phase 2

Pairwise comparison of Inferential statistical Section identification with leading organizations from 5 analysis of an expanded 72 observations from 4 industry sectors (2×5=10 dataset, fewer sections and industry sectors observations) industry sectors involved

Figure 2. Phase Chart

As regards the overall structure of the current chapter, Section 3.1 introduces the software tools for extracting and processing website texts and performing statistical tests, as well as the corresponding descriptive and inferential statistical tests. Next, Section 3.2 explains the selection, sampling and pre-processing of the website texts for performing relevant statistical analyses. Then, Section 3.3 describes the overall analytical framework highlighting the textual features under study. Lastly, Section 3.4 gives a summary of Chapter

3.1 Instrument

The overall process of data processing, management and analysis the current study follows is shown in Figure 3.

Webpage Text Corpus Statistical Analysis Downloading Extraction Compilation

Analyze My Writing Wordcloud.com WebZIP Textise MS Excel Count Wordsworth IBM SPSS

Figure 3. Process Flowchart

First of all, the researcher chose WebZIP 7.0 to download the webpages at the designated levels from the selected websites. This tool can specify the extraction depth of

website texts and minimum intervention is needed in inspecting the extraction results for validity.

Next, an online tool, Textise, was chosen to extract the texts from different website sections, before conducting comparative lexical analyses, including word frequency (Bowker,

2002, p. 75). For targeted text extraction in a website section, the extracted texts were all manually checked to remove quick links and unwanted image captions so as to make sure that only the texts of interest were extracted from the section in question.

Then, Microsoft Office Excel 2016 was chosen to manage and maintain the textual segments. Since the current study compares localized and non-localized English texts extracted from the same website section, the corpus thus compiled needs to differentiate between navigational and content texts, to distinguish different organization types, and to group texts extracted from different website sections. All this metadata information was recorded in separate columns of MS Excel spreadsheets.

The last task for data analysis was performing statistical analysis. As for the tools performing descriptive statistical tests in Phase 1, the researcher chose an online tool,

Analyze My Writing, to calculate the two lexical features under study, the most frequent content words and lexical density. As a supplement to Analyze My Writing, an online word cloud generator, wordclouds.com, was used for generating a visual presentation of word frequency in a given text. In a word cloud, the size of a certain word is proportional to its frequency in the text. As for the measurement of sentence-level features, Count Wordsworth, another online tool, calculated the two sentential features under study, average sentence

length and the percentage of first- and second-person sentences. IBM SPSS 24 was used to perform inferential statistical tests on comparable groups for the purpose of the dissertation.

The type of inferential statistical test applicable for Phase 2 was determined by running an online wizard, Statistical Decision Tree. This tool outputs the recommended test type based on the basic profiles of independent (predictor) and dependent (outcome) variables. In other words, given the numbers of independent and dependent variables, the tool can suggest the applicable statistical test to be performed.

The current study dealt with two predictor variables, Localization Profile (with two levels, Localized and Non-localized) and Organization Type. The analysis in Phase 2 excluded ecommerce websites because leading Chinese ecommerce companies mostly target local markets for the current stage and do not have an English website yet. Therefore, ecommerce as an organization type was discussed in Phase 1 alone, where two leading ecommerce companies were compared to shed a tentative light on this industry sector. The actual number of levels of the predictor variables Organization Type dealt with in Phase 2 depends on the available datasets in equivalent sections for comparison. The sample size for

Phase 2 can only be finalized after the descriptive analysis in Phase 1 (see Section 4.3 about determining the sample size for Phase 2). Next, the input parameter for the number of outcome variables was set at 3, which means that the researcher plans to select three continuous textual-linguistic features as outcome variables for performing inferential statistical tests in Phase 2. Figure 4 shows the summary page of Statistical Decision Tree with the inputs of 2 categorical predictor variables and 3 continuous outcome variables. It can be seen that two-way MANOVA as an inferential statistical test is applicable to the current study.

According to Field (2013), MANOVA can detect group differences on multiple outcome variables as well as the correlation among predictor and outcome variables. As the dissertation studies the variation of multiple textual features across industry and country,

MANOVA can be expected to answer the research questions related to the comparison of localized and non-localized website texts.

Figure 4. Summary Page of Statistical Decision Tree

Based on the grouped comparison of Phase 1, Phase 2 conducted a comparative analysis on an expanded dataset, performing inferential statistical tests on three features to be further discussed in Sections 3.3.1 and 3.3.2.

3.2 Sample Selection and Data Validation

Adopting the strategy of purposeful sampling, the current study collected a selection of website texts from leading organizations representing five industry sectors. As specified in

2017 North American Industry Classification System (NAICS; Executive Office of the

President Office of Management and Budget, 2017), the selected organization types correspond to five industry sectors (enclosed by parentheses): language service providers or

LSPs (Language Translation Services), ecommerce companies (Retail Trade), universities

(Education Services), city governments (Public Administration), and tourism destinations

(Amusement and Recreational Services). The first organization type has the most relevance to

the vocational slant of Translation Studies, while the remaining four are the most popular

research subjects in the existing Information Systems (IS) and marketing literature (Díaz,

Rusu, & Collazos, 2017; Antonucci et al., 2017; Feeney & Brown, 2017; Mele & Cantoni,

2018). In addition, the service-oriented nature of the other four industry sectors makes them

interesting cross-sectional benchmarks for an industry as young as the language industry.

To collect data for Step 1 of the inductive Phase 1, a pair of comparable leading

Chinese and American organizations were selected for each organization type to study their

English-language websites. To choose representative examples from the five organization for paired comparison, business companies, including LSPs and ecommerce, were evaluated for gross revenue, market share and business influence in their home countries; the top universities were selected for their national rankings; and the capital cities of both China and the United States were selected for the study of tourism destination and city government websites to ensure comparability. The organizations thus selected all play an exemplary role in their respective industry sectors and their websites are believed to set the industry standard for their peers. The websites selected for Step 1 of Phase 1 are shown in Table 1.

Table 1. The Selected Localized and Non-Localized English Websites for Step 1 of Phase 1

Organization Localized Non-localized Note Type LSP Pactera Technology TransPerfect Top private LSPs in China and International (http://www.transp the United States (Common erfect.com/) Sense Advisory, 2017)

(https://en.pactera.c om/) Ecommerce Alibaba Amazon Top ecommerce websites in Companies (http://www.aliexpr (https://www.amaz China and the United States ess.com/) on.com/) according to Forbes Global 2000 List of 2017 (Forbes, 2018) University Tsinghua UC Berkeley Top public universities in University (http://berkeley.edu China and the United States, (http://www.tsingh /index.html) both well known for ua.edu.cn/publish/n engineering and business ewthuen/) school. American university ranking is based on the data provided by U.S. News (2018); Chinese university ranking is based on the data provided by topuniversities.com (2018b). Government The city The city Beijing and Washington DC government of government of are the capital city of China Beijing, China Washington DC, and the United States, (http://www.ebeijin USA respectively. g.gov.cn/Governme (https://dc.gov/) nt/) Tourism Beijing Tourism - Washington.org— ibid. Destination The Beijing Official Tourism Municipal Site of Washington Commission of DC Tourism (washington.org) Development (http://english.visit beijing.com.cn/ ) Both the navigational text and the content text were extracted from the selected websites. Both phases ensure a webpage-extraction depth of 2 levels, that is, the texts under study were drawn out from the homepage and all the top-level webpages (one level lower than the homepage) of each selected website. And the subsequent comparisons in Phase 1 all followed the analytic framework as specified in Section 3.1, thus generating the hypotheses to be examined in Phase 2.

The selection criteria of websites for Step 2 of Phase 1 are shown in Table 2 (see

Appendix A for the detailed selection). Only 9 of the leading China-based LSPs as listed in

Common Sense Advisory ranking have English websites, so the sample size for each group was adjusted to 9 to form equal-sized groups. Therefore, a total of 72 (9×4×2) English- language websites (or samples) were selected for the grouped comparison of Phase 1.

Table 2. The Selection Criteria of Localized and Non-Localized English Websites for Step 2 of

Phase 1

Organization Localized Non-localized Selection Criteria Type LSP Top China-based Top US-based LSPs The selection is based LSPs on the global and Asian ranking of LSPs’ gross revenue as of 2017(Common Sense Advisory, 2017a; Common Sense Advisory, 2017b) University Top engineering Top engineering The selection is based universities in China universities in the on the 14th QS World United States University Rankings of 2018 (QS Top Universities, 2018a) Government Major cities in Major cities in the The selection is based China United States on population size as of 2018 (World Population Review, 2018a & 2018b). Tourism Top tourism cities in Top tourism cities in The Most Visited Cities Destination China the United States as of 2017 according to Chinahighlights (2017) and INSIDER (Schmalbruch, 2017) The grouping of the texts extracted from each website was based on the prototypical

superstructure depicted in a previous study (Jiménez-Crespo, 2009), as shown in Figure 5.

Since Jiménez-Crespo’s study was focused on corporate websites alone, the analysis of all the

selected websites in the dissertation, corporate or not, referred to pertinent sections and sub-

sections with necessary revisions and adaptations. The comparative analysis in the current

study was only applied to the textual datasets extracted from equivalent sections in the

localized and non-localized English websites.

Figure 5. The Prototypical Superstructure of Corporate Websites in Jiménez-Crespo’s study (2009).

3.3 A Framework Facilitating Multi-Dimensional Contrastive Analysis

To guarantee apples-to-apples comparisons, both navigational and content texts on the localized websites were compared with their counterparts on the non-localized websites within the same communicative section (see Section 2.1.1 for the definitions of these two text types). The items of interest identified for website comparison were studied for their relative frequencies of occurrence and the context or usage of an occurrence was discussed where applicable. Furthermore, the case-by-case comparison also explored the possibility of grouping occurrences by context or usage.

The theoretical support for taking such a frequency-based approach can be found in contrastive linguistics research, which provides the touchstone for assessing the extent to which typical features of translated texts (Zanettin, 2012, p. 25) are shaped by source language. In addition to studying the influence of Chinese as source language on the text of localized organization websites, the current comparative analysis also evaluated the influence of organization type on the text of both localized and non-localized organization websites.

According to the review of Section 2.1.2, seldom any academic literature published outside China’s publishing circle has dealt with the textual analysis of Chinese organization websites localized into English. Most features the current study deals with are thus derived from the relevant scholarly articles published since 2006, in which year the first published study on Chinese-into-English website translation can be located in CNKI, the leading academic database in China.2 A review of 122 academic articles (including both the Chinese-

language and English-language publications retrieved on Jan 18, 2018) shows that recent

empirical studies of organization website texts localized from Chinese into English mostly

conduct an example-based analysis of translation errors and inadequacy, or attempt to

formulate general translation guidelines or strategies for website text. The dissertation

deviates from previous studies by carrying out a descriptive-comparative analysis, taking into

account the influence of localization process on the product of online organizational

discourse. The following four subsections correspond to the four research questions under

study. The first two, 3.3.1 and 3.3.2, define the specific textual-linguistic features underlying the first two research questions and cite relevant research to support the selection. Based

2 http://oversea.cnki.net/kns55/support/en/about_cnki.aspx

upon a smaller selection of features, Phase 2 provides statistical evidence for answering the

third research question about industry- and language-specific influence (Section 3.3.3).

The comparative analyses were all conducted within equivalent website sections. As an illustration, Figure 5 shows some sections (the second row) and subsections (the third row) of a corporate website.

3.3.1 Terms and lexis.

To begin with, the dissertation analyzed the extent of standardization of navigational

terms and phrases (Jiménez-Crespo, 2009), in particular section titles, e.g. Home, About Us,

and Contact Us. Furthermore, the most frequent content words (Li & Li, 2015) were studied

as well.

As the third and the last item for lexical-level analysis, the information load of different sections in localized and non-localized websites was studied by calculating the percentage of lexical or content words in a text (Baker, 1996), or lexical density (Tang, 2012).

Lexical or content words are nouns, adjectives, most verbs, and most adverbs. Grammatical or functional words, which constitute the rest of a text, are pronouns, prepositions, conjunctions, auxiliary verbs, some adverbs, determiners, and interjections. Laviosa’s (2002, p. 55) reservation about previous empirical findings of lexical density lies in a concentration of Romance languages as source languages for the translation. Therefore, the current study analyzing the web texts localized from Chinese is expected to shed new light on the empirical studies of lexical density.

To recap, the lexical-level analysis for Phase 1 covered three features: (1) the standardization of navigational expressions, (2) the most frequent content words, and (3) lexical density.

3.3.2 Syntax, grammar and discourse.

Next, the website texts were analyzed over the sentence level. It can be intuitively acknowledged that website texts feature simpler sentences, shorter paragraphs and less complex grammatical structures than texts in conventional print. For an empirical insight into website texts, Phase 1 studied the syntactic patterns of localized and non-localized organization websites by specifically analyzing: (1) average sentence length (Yang, 2013;

Zhou, 2015; Zhu, 2013; Ma, 2014; Li, 2014; Jiang, 2013; Li &Li, 2015; Zhang, 2013; He,

2008), and (2) the relative frequency of first- and second-person sentences (Yang, 2013;

Zhou, 2015; Li & Li, 2015; Lu, 2012; He, 2008; Peng, 2013; Jiang, 2013; Yang, 2016; Guo,

2010; Wang, 2013; Cheng, 2013).3

These feature-based comparisons of localized and non-localized websites in Phase 1 can serve as a partial snapshot of the current cyber ecosystem to inform localization trainers, trainees, and practitioners. The multi-faceted research findings from different website sections can be later fed into user-oriented studies to improve website usability. Building on the results of the analysis of this dissertation, future user experiments can target specific sections of localized and non-localized English websites to collect data about user reception.

Following the small-scale textual analysis in Phase 1, Phase 2 ran an inferential statistical test on an expanded textual dataset, involving a larger number of organization

3 Note that the former refers to sentences with such words as I, we, you, me, us, my mine, your, yours, our, and ours, while the latter refers to those with such words as he, she, it, they, his, her, its, hers, theirs 59

websites. Phase 2 intends to quantitatively test the hypotheses induced from the paired and

grouped comparisons in Phase 1. In summary, the features studied in the two phases are marked

with an asterisk (“*”) as shown in Table 3. One of the features, the most frequent content words,

was studied at Step 2 of Phase 1 alone, since the sample size for paired comparison is too small

for frequency count.

Table 3. The Items of Interest under Study in Phase 1 and 2

Phase 1 - Qualititative & Phase 2 - Inferential Items of Analysis Descriptive Statistical Analysis Statistical Analysis Step 1 - Paired Step 2 - Grouped Comparison Comparison Standardization of navigational L1 * * t e xt

Note: the sample Lexical The most frequent content L2 size is too small for * words Analysis frequency count

L3 Lexical density * * *

S1 The average sentence length * * * Sentential Analysis The relative frequency of first- S2 * * * and second--personal pronouns

3.3.3 Industry- and language-specific effect.

The qualitative and descriptive statistical analysis conducted in Phase 1 facilitate both within- and cross-industry comparisons of representative organization websites. Furthermore, treating Organization Type as a categorical predictor variable, Phase 2 can provide statistical evidence for evaluating the industry-specific influence on the three lexical and sentential features under study.

The MANOVA test can answer the question of whether the combination of multiple outcome variables, specifically the three textual-linguistic variables under study in Phase 2, vary significantly with respect to the predictor variables (Localization Profile and Organization

Type) in the current study. MANOVA can also statistically identify any interaction among

predictor and outcome variables.

3.4 Summary

To begin with, this chapter discussed the theoretical rationale for combining qualitative and quantitative analysis to best fulfill the purpose of the current descriptive study based on textu comparison. After explaining the guiding approach, the researcher briefly explained the overall process of dual-phase data analysis that underlies the current study. Section 3.1 clarified the overall research procedure and explained different software tools facilitating each step of data processing. Section 3.2 then introduced the process of data selection and pre-processing,

highlighting the sampling criteria and considerations for performing statistical tests. Equipped

with the textual data ready for applicable statistical analysis, Section 3.3 described a multi-

dimensional analytical framework the dissertation followed and fleshed it out with lexical and

sentential features covered by the two phases of data analysis.

Adopting the methodology devised in Chapter 3, the next chapter will present and discuss the results for applicable website sections in different analytical dimensions. The observations will be accompanied by an explanation of the findings. The descriptive approach

taken by the current study, as Crystal (2006) argues, describes the variations in usage found

within a language, and explains why certain variations exist.

IV. Results and Analysis

This chapter puts into practice the methodological framework and text-analysis tools

highlighted in Chapter 3 by presenting and interpreting the results produced in both phases.

Section 4.1 and 4.2 explain all the analysis results for the paired and grouped comparisons in

Phase 1, respectively. The subsections under both sections all correspond to the industry

sectors under analysis, in addition to cross-industry comparisons. Next, Section 4.3

introduces the procedure of performing the MANOVA test in Phase 2, studies the statistical results, and summarizes the findings to explore the existence of an English variant in organization website text localized from Chinese. Lastly, Section 4.4 concludes this chapter by giving a summary.

All the website texts under discussion were retrieved on Jan 27, 2018. The current study highlights comparable and available website sections typically undergoing less frequent updates, in particular About Us, so as to minimize the effect of time sensitivity on empirical studies of websites.

The identification of comparable website sections is the first step to conducting comparisons, paired or grouped, within each industry sector. This is also the precondition for comparing localized and non-localized website texts, that is, the texts for comparison should come from the same website section. After identifying the sections shared by localized and non-localized websites, the researcher distinguished frequently updated sections from less frequently updated ones, and only looked at the latter for the current study due to the consideration of time sensitivity. This process of section identification was repeated at the beginning of every within- and cross-industry comparison in the study.

4.1 Step 1 of Phase 1: Paired Comparisons

This section presents and discusses the comparison results of ten organization websites representing five industry sectors, each involving one localized website and one non-localized website for comparison. See Table 1 for a list of these ten websites involved in

paired comparison.

4.1.1 LSP: Pactera vs. TransPerfect.

The sitemaps of the two LSP websites showed the following shared sections: (1)

company profile, giving an overview of the LSP, including history and mission statement, (2)

services, listing the types of services the LSP offers, (3) industries served, listing the

industries the LSP has served, (4) technology, showcasing the technology expertise of the

LSP, (5) featured client solutions, highlighting success stories and case studies, (6) contact us,

a display of direct contact information, (7) join us, posting job vacancies, (8) news and

events, an update on past, present and upcoming company news and events, (9) privacy

policy, a legal document explaining how the company gathers, uses, discloses, and manages

client data, (10) industry blogs and resources, facilitating stakeholder education, (11) find

local office, a display of contact information for the company’s local offices, and (12)

sitemap, showing the directory structure of all the webpages hosted by the LSP website. All

of these sections were analyzed for navigational text. In addition, the sections chosen for the

paired comparison of content text were (1), (3), (4), (6), (7), and (9), due to the fact that these

sections were found to contain comparable content text undergoing less frequent updates.

Table 4 is a crosstab template listing all the textual features under analysis for the

selected website sections (L: Localized Pactera website; NL: Non-Localized TransPerfect website), presenting an overview of all the items under comparison for the two LSP websites.

Table 4. Crosstab Template Listing All the Textual Features under Analysis for the Chosen

LSP Website Sections

Communicative Section Company profile Industries served Technology Contact us Join us Privacy policy Company L NL L NL L NL L NL L NL L NL Standardization of L1 Lexical navigational text Analysis L3 Lexical density

The mean sentence S1 length Sentential Analysis The relative frequency S2 of first- and second- person sentences

As shown in Table 4, a total of four textual features, including two lexical ones and

two sentential ones, were analyzed for comparable sections in the two LSP websites selected

for paired comparison. And this template was applied to all the other four industry sectors

under analysis to facilitate the cross-industry comparison in Section 4.1.6, though there

existed some variation in comparable website sections, since it is understandable that

organization website from different industry sectors do not necessarily share an identical set

of comparable sections.

Table 5 lists the lexical items fulfilling similar navigational purposes in the localized

and non-localized LSP websites (L: Localized Pactera website; NL: Non-Localized

TransPerfect website). Three points of findings related to commonalities in navigational text

can be seen in Table 5. The first observation was that all the navigational texts linking to a

section on a different webpage or a location on the same webpage contain no more than three

words. The longer exceptions can only be found at the bottom of the webpage, usually

repeating the links to important sections listed at page top.

Secondly, the two sections with identical lexical representation were Industries and

Technology, suggesting that these two communicative blocks saw a relatively high level of

navigational-text standardization in both LSP websites.

The last finding was the overall absence of “Home” from both website homepages,

though on the localized Pactera website, “home” can still be found as a text link in the breadcrumb4 trail at the top of each subpage to direct the visitor back to the homepage. In

any case, it seems that a “Home” icon or text link is dispensable for an LSP website since a

click on the company logo at the top-left corner of the page typically directs visitors back to

the homepage, though more empirical evidence is needed for further generalization. These

features of navigational text will be revisited in the subsequent within- and cross-industry comparisons.

4 In the context of website design, breadcrumbs allow users to identify their current location within the system by providing a clickable trail of proceeding pages to navigate by. 65

Table 5. The Lexical Items of Different Sections of Pactera and TransPerfect Websites

Communicative Section L NL

Company profile Company Who We Are

Services (Multiple Sections) What We Do

Industries served Industries

Technology Technology

Featured client solutions Our Work Client Solutions Contact Us/Work with Contact us Get in Touch Us/ Connect with Us Join us Careers & Culture Join Our Team

News and events News & Press Press Center

Industry blogs and resources Insights & Trends Thought Leadership

Find local office Find Locations Find Your Local Office

Sitemap Site Index Sitemap

In terms of differences in navigational text, the first- and second-person sentences appeared more frequently in the navigational text of non-localized TransPerfect website than in that of localized Pactera website. This can be attributable to the influence of Chinese as source language; Chinese language tends to avoid conversational voice in formal writing, in particular organization-specific descriptions. Secondly, the section Contact Us was found to be an interesting testing field for identifying the target audience the two LSP websites address. For example, localized Pactera website set aside separate Contact Us links for different audiences, including interested job seekers, prospective clients, and visitors interested in industry updates. Although these separate links all pointed to the webpage of a contact form, the approach showed the website’s intention of addressing different stakeholders. Similar in rationale yet a little different in implementation, the homepage of

non-localized TransPerfect website presented a prominent, direct link for prospective clients

(“Get in Touch”), with separate subpages dedicated to job seekers (“Join Our Team”) and

other interested visitors (“Connect with Us”).

To conclude the discussion on navigational text, Table 6 shows the sections found in

one LSP website alone (L: Localized Pactera website; NL: Non-Localized TransPerfect

website). A close look at these website sections indicates that the two LSP websites have

developed different strategic focus areas. The localized Pactera website strives at forging a

trustful corporate image for investors and clients, with the online publication of the code of

business ethics for both the company and its suppliers, while the non-localized TransPerfect

website places more attention on its technology advantage and industry expertise, by

highlighting technology-related sections on its homepage. This difference can be explained

by the variation in the two LSP’s service portfolios as shown on their websites. The localized

Pactera website offered a variety of technology solutions, among which language services

was termed “globalization solution,” meaning that language services is just one line of its

business. This can be further illustrated by a tagline on the localized Pactera website, “more

than a technology company.” On the other hand, the non-localized TransPerfect website is more reliant on language services for its business development, so promoting technology expertise is expected to attract prospective client and collaborators.

Table 6. Distinct Sections in Paired LSP-website Comparison

L NL Code of Ethics The TransPerfect Advantage Subscribe (Newsletters) GlobalLink (A featured technology Events of system integration)

Accordingly, all the subsequent comparisons of navigational text within and across

industry sectors will also address the abovementioned topics: (1) word count of navigational

text, (2) most standardized website sections, (3) presence of “Home,” (4) first-, second-, and

third-person points of view, (5) target website audience as suggested by the navigational text,

and (6) distinct website sections.

The next analysis of paired LSP comparison studies the lexical density of content text.

Table 7 shows the lexical density of the LSP website sections available for content-text

comparison (L: Localized Pactera website; NL: Non-Localized TransPerfect website). In

general, the lexical density of the non-localized TransPerfect website was higher than that of

the localized Pactera website, but it would be hasty to apply this observation to localized and

non-localized website at large, as some website sections featured more levels of webpages

than others. A case in point is “Technology.” As a first-level webpage (one level lower than

the homepage) on non-localized TransPerfect website, “Technology” text consisted of a list of phrases, resulting in a lexical density of 100%. The only section where the lexical density of the localized Pactera website was higher than that of the non-localized TransPerfect website was “Join Us,” which has largely to do with the fact that this section in the non- localized Transperfect website featured multiple short sentences while its counterpart in the localized Pactera website was simply a long sentence. This shows that lexical density in some way correlates to average sentence length. The topic of lexical density will be revisited in subsequent comparisons so as to explore how strong an indicator lexical density is of lexical variety and creativity for the content text of a website.

Table 7. Lexical Density of the LSP Website Sections Available for Content-text Comparison

Communicative Section L (%) NL (%) Company profile 63.3 64.5 Industries served 68.6 77.0 Technology 69.1 100.0 Contact us 59.4 77.0 Join us 76.0 64.0 Privacy policy 51.4 59.1

As for sentence-level analysis, Table 8 shows the average sentence length of the LSP website sections available for content-text comparison (L: Localized Pactera website; NL:

Non-Localized TransPerfect website). The two sections of the non-localized TransPerfect website are marked with “N/A” since most of the section texts took the form of one-word nouns or two-word noun phrases, which is not applicable for calculating sentence length. In a way, this suggests that non-localized websites may enjoy greater freedom of text structuring and experiment with a greater variety of forms of expression. In most website sections under comparison, the non-localized TransPerfect website had longer sentences than the localized

Pactera website. A review of individual texts points to one possible explanation, that is, each section of the non-localized TransPerfect website strives at addressing multiple audience types with parallel sentence structures, such as “If you are …, … If you are…,” thus rendering the section wordier.

Table 8. The Average Sentence Length of the LSP Website Sections Available for Content- text Comparison

Communicative Section L NL Company profile 18.3 19.0 Industries served 24.5 N/A Technology 15.7 N/A Contact us 12.5 15.7 Join us 16.0 15.3 Privacy policy 19.8 23.5

Table 9 shows the relative frequency of first- and second-person sentences in the LSP

website sections available for content-text comparison (L: Localized Pactera website; NL:

Non-Localized TransPerfect website). Similar to the analysis of Table 8, the sections of the

non-localized TransPerfect website marked with “N/A” because they are not applicable for

sentence-level analysis. In general, the non-localized TransPerfect website saw a higher

relative frequency of first- and second-person sentences than the localized Pactera website as one may expect beforehand. And most sections of the non-localized website were found to be

dominated by first- and second-person sentences. This indicates that the non-localized

website embraces a more conversational voice in general than its localized counterpart. The

only interesting exception is Privacy Policy, where the non-localized TransPerfect website

saw the absence of “we” in place of company name for self-representation.

Table 9. The Relative Frequency of First- and Second-person Sentences in the Website

Sections Available for Content-text Comparison

Communicative Section L (%) NL (%) Company profile 57.0 100.0 Industries served 45.0 N/A Technology 79.0 N/A Contact us 66.0 100.0 Join us 100.0 100.0 Privacy policy 94.0 68.0

In summary, the researcher studied the following features of navigational text and

content text in the paired comparison of LSP websites: (1) word count of navigational text,

(2) most standardized website sections; (3) presence of “Home,” (4) first-, second-, and third- person points of view in the navigational text, (5) target website audience, as suggested by the navigational text, (6) sections found in one website alone, (7) the lexical density of content text, (8) average sentence length of the content text, and (9) relative frequency of first- and second-person sentences in the content text. These features will be revisited in the subsequent paired comparisons for the other industry sectors as well as the grouped comparisons in Section 4.2.

4.1.2 Ecommerce: AliExpress (Alibaba) vs. Amazon.

The two ecommerce websites under analysis shared the following sections: (1) product classification, listing the types of products sold online so that a customer can quickly locate the item of interest, (2) items to explore, listing popular product categories to rouse a potential customer’s interest, (3) featured stores, highlighting certain stores to promote storewide sales, (4) deals, promoting certain product items for quick sales, (5) recommendations, recommending product items based on the customer’s history of searching, browsing, and ordering so as to implement targeted marketing, (6) call for partners, inviting business partners to promote the links to products in return for commercial incentives, (7) help, an online center of customer service to answer questions about the process of online transactions, (8) terms and conditions of use, listing the rules the visitor must abide by in order to use website services, and (9) privacy policy, a legal document explaining how the site uses, discloses, and manages user data. All of these sections were

analyzed for navigational text. In addition, the sections chosen for the paired comparison of

content text were (1), (8), and (9), because these sections were found to contain comparable

content texts undergoing less frequent updates.

Table 10 is a crosstab template listing all the textual features under analysis for the

selected website sections (L: Localized AliExpress website; NL: Non-Localized Amazon website), presenting an overview of all the items under comparison for the two ecommerce websites. Note that the section “product classification” was only studied for the qualitative analysis of navigational text, since its content text consisted of words and phrases rather than complete sentences, thus not applicable for either lexical-density calculation or sentence-level

analysis.

Table 10. Crosstab Template Listing All the Textual Features under Analysis for the Chosen

Ecommerce Website Sections

Product Terms and Communicative Section Privacy policy classification conditions of use Company L NL L NL L NL Standardization of L1 Lexical navigational text Analysis L3 Lexical density N/A N/A

The mean sentence S1 N/A N/A length Sentential Analysis The relative frequency S2 of first- and second- N/A N/A person sentences

Table 11 shows the lexical items for the navigational text in the localized and non- localized ecommerce websites (L: Localized AliExpress website; NL: Non-Localized

Amazon website). Firstly, the word count of navigational text on the non-localized Amazon

website in general was a little more than the localized AliExpress website, which is

attributable to four- and five-word lexical items found in some sections of the non-localized

Amazon website. Furthermore, it is the stronger presence of first- and second-person points

of view that results in the longer lexical items featuring the non-localized Amazon website, such as “We Have Recommendations for You,” “Get to Know Us,” and “Let Us Help You.”

Secondly, the most standardized website section was Help for customer service. Thirdly, neither of the websites included an explicit text for navigating back to the homepage, except for the homepage-implying company logo located at the top left corner of the webpage.

Fourthly, the non-localized Amazon website found a stronger presence of first- and second- person voice than the localized AliExpress website. Finally, most parts of both websites directly addressed current and prospective customers, with only one or two less prominent sections addressing prospective business partners, and only one section on the non-localized

Amazon website alone addressed job seekers.

Table 11. The Lexical Items of Different Sections of AliExpress and Amazon Websites

Communicative Section L NL

Product Classification Categories Departments

Items to Explore Inspiration New and Interesting Finds

Featured Stores Spotlight Stores (...) Bestsellers

Deals Flash Deals/$5 Deals Today's Deals

Recommendations More to Love We Have Recommendations for You

Call for Partners Partner Promotion Get to Know Us

Help Help Help (under Let Us Help You)

Terms and Conditions of Use Terms of Use Conditions of Use

Table 12 shows the sections identified in one website alone. In general, the table indicates that the localized and non-localized ecommerce websites implement different promotional strategies due to different cultural and business circumstances. We can see that the localized AliExpress website introduced website visitors to its mobile apps in order to boost sales with “on-the-move” ordering and payment (“Save big on our app!”), emphasized the time criticalness of deals (“LIVE,” a section for sellers showing their products in form of live demos, with a count-down clock suggesting the urgency of placing an order before the deal is gone). The localized AliExpress website also addressed the prospective buyer’s concerns of counterfeit products sold via international ecommerce channels (“How to Buy,”

“Intellectual Property Protection,” and “Law Enforcement Compliance Guide”) and built customer trust with a presentation of its own competitive advantages (Why Us). In contrast, the non-localized Amazon website exploited business possibilities in cultural trends and events (“Gift Cards” and “Registry,” targeting those interested in buying gifts for weddings or baby showers) and strived at strengthening collaboration with sellers (“Sell;” note that at the time of writing, the localized AliExpress website has not yet opened its Business-to-Client, or

B2C, website to international sellers, although more extensive overseas collaboration is under way, according to Alibaba’s Chinese-language website.5)

5 http://activities.aliexpress.com/adcms/seller-aliexpress-com/about/newbie.php

Table 12. Distinct Sections in Paired Ecommerce-website Comparison

L NL Save big on our app! Brand Zone Why Us Gift Cards LIVE Registry How to Buy (Buyer Protection) Sell Intellectual Property Protection Law Enforcement Compliance Guide

Table 13 shows the lexical density of the ecommerce website sections available for content-text comparison (L: Localized AliExpress website; NL: Non-Localized Amazon website). In general, the non-localized Amazon website had higher lexical density than the localized AliExpress website in the two sections applicable for paired comparison, “Terms and Conditions of Use” and “Privacy Policy.” Within the first two levels of webpages that are of interest for the current study, only two sections, “Terms and Conditions of Use” and

“Privacy Policy,” were found to contain comparable texts, since the two ecommerce websites both highlighted thumbnail pictures of deals and products on top- and first-level webpages.

Table 13. Lexical Density of the Ecommerce Website Sections Available for Content-text

Comparison

Communicative Section L (%) NL (%) Terms and Conditions of Use 54.7 55.8 Privacy Policy 52.7 58.9

Table 14 shows the average sentence length of the ecommerce website sections applicable for paired comparison (L: Localized AliExpress website; NL: Non-Localized

Amazon website). As can be seen from the table, one section of the localized AliExpress

website on average has longer sentences than that of the non-localized Amazon website and

the opposite applied to the other section under study.

Table 14. The Average Sentence Length of the Ecommerce Website Sections Available for

Content-text Comparison

Communicative Section L NL Terms and Conditions of Use 20.3 21.1 Privacy Policy 21.0 17.7

Table 15 shows the relative frequency of first- and second-person sentences in the ecommerce website sections available for content-text comparison (L: Localized AliExpress website; NL: Non-Localized Amazon website). It can be seen that first- and second-person

voice dominated the two sections in both ecommerce websites.

Table 15. The Relative Frequency of First- and Second-person Sentences in the Ecommerce

Website Sections Available for Content-text Comparison

Communicative Section L (%) NL (%) Terms and Conditions of Use 85.0 87.0 Privacy Policy 94.0 92.0

4.1.3 University: Tsinghua vs. UC Berkley.

A comparison of the overall university-website structure shows the commonly shared

sections as follows: (1) university profile, giving a brief overview of the university, including

history, important figures and facts, (2) admissions, policies and forms for prospective

students interested in applying to the university, (3) academics, introducing degree and non-

degree programs offered by schools and departments, (4) research, highlighting the profile of

research programs supported by faculty members and research labs, (5) campus life,

introducing on-campus services and events open to students, (6) news, a regular update on

campus news as well as the media coverage of the university, (7) join us, posting job

vacancies, (8) contact us, displaying contact information to the general public, and (9) call for

donations. All of these sections were analyzed for navigational text. In addition, the sections

chosen for the paired comparison of content text were (1), (2), and (5), because these sections

were found to contain comparable content texts undergoing less frequent updates.

Table 16 is a crosstab template listing all the textual features under analysis for the

selected website sections (L: Localized Tsinghua website; NL: Non-Localized UC Berkeley website), presenting an overview of all the items under comparison for the two university websites.

Table 16 Crosstab Template Listing All the Textual Features under Analysis for the Chosen

University Website Sections

About us-University Campus Life-Overview of Admissions- Communicative Section Overview Student Organizations Undergraduate University L NL L NL L NL Standardization of Lexical L1 navigational text Analysis L3 Lexical density The mean sentence S1 length Sentential The relative frequency Analysis S2 of first- and second- person sentences Table 17 shows the lexical items for the navigational text in the localized and non-

localized university websites (L: Localized Tsinghua website; NL: Non-Localized UC

Berkeley website). Firstly, all the navigational texts featured a word count of 1 or 2, and the

only three-word exception was found at the bottom half of the homepage of the localized

Tsinghua website. Secondly, the university-website pair saw the most standardized section titles of all three website pairs that have been evaluated thus far, including About Us,

Admissions, Research, News, and Join Us. In the localized Tsinghua website, “International”

in place of Academics section suggests that L specifically addressed international students

and scholars, while the non-localized UC Berkeley website took on a more general tone.

Thirdly, neither of the university websites offered an icon- or button-based navigation cue for homepage. Fourthly, it is interesting to note from this paired comparison that the university website, localized or non-localized, is likely to be a most detached type of organization website, which can be illustrated by no or weak presence of first- and second-person voice in the navigational text. Lastly, it can be seen that the non-localized UC Berkeley website specified separate gateways for students, faculty and staff members, parents, and alumni, while the localized Tsinghua website had no such explicit design, as the two sections,

“faculty” and “alumni,” were located in the navigation bar together with other sections failing to explicitly addressing an audience group.

Table 17. The Lexical Items of Different Sections of Tsinghua and UC Berkeley Websites

Communicative Section L NL

About Us About

Admissions Admissions

Academics International Academics

Research Research

Campus Life Campus Campus Life

News News

Join Us Jobs

Call for Donations Giving to TH Give

To conclude the discussion on navigational text, Table 18 shows the sections identified in one website alone (L: Localized Tsinghua website; NL: Non-Localized UC

Berkeley website). Recall that the non-localized UC Berkeley website featured the targeted grouping of website sections that addressed different audiences, including students, faculty and staff, parents and alumni. Next, the information on campus tours was highlighted as a separate section on the UC Berkeley homepage rather than Tsinghua homepage, which in a way shows UC Berkeley’s motivation of reaching out to prospective students and the community. In addition, the directory in the non-localized UC Berkeley website, serving the purpose of displaying the contact information the faculty, staff and students agree to share in public, was not found in the localized Tsinghua website, which suggests that maintaining a 79

collective database of personnel contact information is not a customary practice of such

Chinese university websites as Tsinghua. And similar to the people directory, UC Berkeley rather than Tsinghua offered an A-Z directory of subsites under the mainsite. Furthermore, L did not contain the subsection “Advising and Tutoring,” which was promoted in NL as an important service offered to students. Lastly, in the Research section, the localized Tsinghua website stressed IP (intellectual property) protection and international cooperation, while the non-localized UC Berkeley website promoted the initiative of undergraduate research. One possible explanation for this difference is that L intended to exhibit its academic openness to attract the attention of the researchers worldwide via its English website while NL hoped to attract prospective students with competitive research programs so as to offer students an edge in future job market.

Table 18. Distinct Sections in Paired University-website Comparison

L NL Student|Faculty&Staff|Parents Visit Directory Research - Intellectual Property, Research Cooperation, Academics - Advising and Tutoring International Communication Websites A-Z Research - Undergraduate Research

Table 19 shows the lexical density of the university website sections available for content-text comparison (L: Localized Tsinghua website; NL: Non-Localized UC Berkeley website). Two subsections of the localized Tsinghua website, “Undergraduate” and

“Overview of Student Organization” had higher lexical density than those of the non-

localized UC Berkeley website, while the university profile of the former had lower lexical

density than that of the latter.

Table 19. Lexical Density of the University Website Sections Available for Content-text

Comparison

Communicative Section L (%) NL (%) About us-Overview 56.7 58.9 Admissions-Undergraduate 64.1 62.7 Campus Life-Overview of 77.8 67.6 Student Organizations Table 20 shows the average sentence length of the university website sections

available for content-text comparison (L: Localized Tsinghua website; NL: Non-Localized

UC Berkeley website). In general, the three comparable sections of the localized Tsinghua

website on average had longer sentences than those of the non-localized UC Berkeley

website.

Table 20. The Average Sentence Length of the University Website Sections Available for

Content-text Comparison

Communicative Section L NL

About us-Overview 19.8 14.3

Admissions-Undergraduate 30.6 13.7 Campus Life-Overview of 24.5 16.6 Student Organizations Table 21 shows the relative frequency of first- and second-person sentences in the

university website sections available for content-text comparison (L: Localized Tsinghua website; NL: Non-Localized UC Berkeley website). The sections under study of the localized

Tsinghua website contained no first- or second-person sentences, in marked contrast to the

equivalent UC Berkeley website sections which were dominated by first- or second-person sentences.

Table 21. The Relative Frequency of First- and Second-person Sentences in the University

Website Sections Available for Content-text Comparison

Communicative Section L (%) NL (%)

About us-Overview 0 71

Admissions-Undergraduate 0 85 Campus Life-Overview of 0 100 Student Organizations 4.1.4 Government: Beijing vs. Washington DC.

The overall structures of the two municipal government websites showed the

commonly shared sections as follows: (1) about us, the profile of the website, (2) education,

an introduction to educational resources accessible to city residents, (3) news & events, (4)

feedback, (5) FAQ (frequently asked questions), (6) privacy policy, and (7) terms and

conditions of use. All of these sections were analyzed for navigational text. In addition, the

sections chosen for the paired comparison of content text were (1), (6), and (7), because these

sections were found to contain comparable content texts undergoing less frequent updates.

Table 22 is a crosstab template listing all the textual features under analysis for the

selected website sections (L: Localized Beijing government website; NL: Non-Localized DC government website), presenting an overview of all the items under comparison for the two government websites.

Table 22. Crosstab Template Listing All the Textual Features under Analysis in the Chosen

Government Website Sections

Terms and Communicative Section About us Privacy policy conditions of use Gove rnme nt L NL L NL L NL Standardization of Lexical L1 navigational text Analysis L3 Lexical density The mean sentence S1 length Sentential The relative frequency Analysis S2 of first- and second- person sentences Table 23 shows the lexical items for the navigational text in the localized and non-

localized government website (L: Localized Beijing government website; NL: Non-Localized

DC government website). Firstly, the word count of the non-localized DC government

website was a little more than that of the localized DC government website, which was largely contributed by a stronger presence of three- and four-word lexical items. Secondly, the different wording of comparable sections fulfilling similar communicative purposes can be found in all the sections under comparison. Thirdly, the localized Beijing government website featured explicit navigation to the homepage by opening a new window showing the website homepage at a click of the “Home” button, while the non-localized DC government website had no such design. Fourthly, just like the pair of university websites in the previous analysis, both of the government websites were dominated by the third-person voice in the navigational text. As a final note on the discussion of navigational text, it is worth noting that for the Education section, “Study” on the localized Beijing government website focused on the introduction of university programs or higher education services to motivate university- age international students to come to study in Beijing, while “Education” on the non-

localized DC government website suggested an all-round purview of education (including K-

12 and post-secondary) mostly targeting local residents. As for target audiences, while the localized Beijing government website targeted temporary residents, travelers, students, and prospective business partner, the non-localized DC government website targeted local residents, travelers, and job seekers.

Table 23. The Lexical Items of Different Sections of Localized and Non-localized

Government Websites

Communicative Section L NL

About us About Us About DC.Gov

Education Study Education

News & Events Official Activities | Mayor's Bulletin News & Events | Featured News

Feedback Feedback Feedback, Complaints, and Appeals

FAQ Q&A Popular Searches

Terms and conditions of use Copyright Terms and Conditions

To conclude the discussion on navigational text, Table 24 shows the sections identified in one website alone (L: Localized Beijing government website; NL: Non-

Localized DC government website). It is clear that the localized Beijing government website mainly targeted international visitors by highlighting those sections that were of potential interest to international visitors, including “Visa,” “Cooperation,” “Recruitment of Experts,” as well as a spotlight section about visiting leaders and honorary citizens. As will be seen in the subsequent grouped comparisons of municipal government websites, “Sister cities” was a

section highlighted by most municipal government websites, since it is intended to reflect an

active role the city government plays in promoting international communication. Also,

“Surveys” can be viewed as another way of collecting feedback for the localized Beijing

government website to reach out to English-speaking website visitors. On the other hand, it can be seen that the non-localized DC government website featured separate gateways so that different audiences can be directed to the most relevant website sections.

Table 24. Distinct Sections in Paired Government-website Comparison

L NL Visa Sister Cities Residents | Government | Visitors | Jobs | Cooperation Online Services | Media & Communication Recruitment of Experts District Initiatives Visiting Leader | Honorary Citizen Sitemap Surveys Table 25 shows the lexical density of the government website sections available for content-text comparison (L: Localized Beijing government website; NL: Non-Localized DC government website). In general, the localized Beijing government website had higher lexical density than the non-localized DC government website for the three sections in question.

Table 25. Lexical Density of the Government Website Sections Available for Content-text

Comparison

Communicative Section L (%) NL (%) About us 64.5 58.1 Privacy policy 59.4 58.1 Terms and conditions of use 82.5 51.0

Table 26 shows the average sentence length of the government website sections available for content-text comparison (L: Localized Beijing government website; NL: Non-

Localized DC government website). The localized Beijing government website on average

had shorter sentences than the non-localized DC government website for the three sections in

question.

Table 26. The Average Sentence Length of the Government Website Sections Available for

Content-text Comparison

Communicative Section L NL About us 13.7 14.0 Privacy policy 15.6 16.0 Terms and conditions of use 8.4 22.6

Table 27 shows the relative frequency of first- and second-person sentences in the

government website sections available for content-text comparison (L: Localized Beijing government website; NL: Non-Localized DC government website). Both websites had a relative high percentage of first- and second-person sentences, except for Terms and

Conditions of Use section in the localized Beijing government website, which in a few sentence fragments introduced the relevant organizations and institutions involved in website design and development, thus claiming website copyright. On the whole, the non-localized

DC government website saw a stronger presence of first- and second-person voice than the localized Beijing government website.

Table 27. The Relative Frequency of First- and Second-person Sentences in the Government

Website Sections Available for Content-text Comparison

Communicative Section L (%) NL (%) About us 80 82 Privacy policy 74 85 Terms and conditions of use 0 78

4.1.5 Tourism destination: Beijing vs. Washington DC.

The overall structures of the two tourism-destination websites showed the commonly shared sections as follows: (1) recommended activities, an introduction to popular things to in the tourism destination, (2) accommodation, recommending places of different standards to stay, (3) routes and tours, recommending travel itineraries to accommodate varying traveler needs, (4) neighborhoods, introducing nearby tourist attractions, (5) transportation, providing information on how to travel to and around the tourism destination, (6) events, introducing the seasonal activities and events held in the tourism destination, (7) news, a regular update on the local travel news, (8) about us, a profile of the tourism promotion organization sponsoring the website, and (9) contact us, providing contact information of the sponsoring organization. All of these sections were analyzed for navigational text. In addition, the

sections chosen for the paired comparison of content text were “About Us” and “City Facts”

(a subsection under “About Beijing” on Beijing tourism website and under “Press” on DC tourism website), because these sections were found to contain comparable content texts undergoing less frequent updates.

Table 28 is a crosstab template listing all the textual features under analysis for the selected website sections (L: Localized Beijing website; NL: Non-Localized DC website), presenting an overview of all the items under comparison for the two tourism-destination websites.

Table 28. Crosstab Template Listing All the Textual Features under Analysis for the Chosen

Website Sections

Communicative Section About us City facts Tourism Destination L NL L NL Standardization of Lexical L1 navigational text Analysis L3 Lexical density The mean sentence S1 length Sentential The relative frequency Analysis S2 of first- and second- person sentences

Table 29 shows the lexical items for the navigational text in the localized and non- localized tourism website (L: Localized Beijing website; NL: Non-Localized DC website).

Firstly, the average word count of the non-localized DC website was a little more than that of the localized Beijing website, largely contributed by three-word lexical items. Secondly, both websites saw navigational-text standardization for two sections, “Recommended Activities”

and “Events.” Thirdly, as for homepage navigation, the localized Beijing website featured

explicit navigation to the homepage by opening a new window showing the website

homepage at a click of “Home” button, while the non-localized DC website had no such

design. Lastly, the presence of first- and second-person sentences did not differ very much

between the two websites, as the major sections of both websites were all dominated by third-

person voice.

Table 29. The Lexical Items of Different Sections of Beijing and DC Tourism Websites

Communicative Section L NL

Recommended Activities Things to Do

Accommodation Accommodation Places to Stay

Routes and tours Routes & Strategy Tours & Sightseeing

Neighborhoods Around Beijing Neighborhoods

Transportation Transportation Getting Around DC

Events Events DC Insider Newsletter (for email News News subscription) About Us About Us About Desitnation DC

To conclude the discussion on navigational text, Table 30 shows the sections identified in one website alone (L: Localized Beijing website; NL: Non-Localized DC website). The localized Beijing website was focused on visitor education by promoting the initiative of tourism-brand ambassador and introducing the tips on travelling in China and learning Chinese language. Also, it encouraged the website visitors to relate to the personal stories told by international traveler blogs about their interesting experiences in China. While the localized Beijing website targeted interested international travelers, the non-localized DC website featured the targeted grouping of different sections for multiple audiences, including visitors, meeting organizers, travel agencies, and media. In addition, the non-localized DC website highlighted deals and free attractions to attract prospective visitors, and the section

“Careers” was dedicated to job seekers.

Table 30. Distinct Sections in Paired Tourism-website Comparison

L NL Visit DC | Meetings | Travel Trade | GDP Programs Members | Press | Book (button) Learn Chinese Deals Tips (travel essentials) Free Attractions Blog (Travelogue) Careers Table 31 shows the lexical density of the tourism website sections available for content-text comparison (L: Localized Beijing website; NL: Non-Localized DC website). It can be seen that the non-localized DC website had higher lexical density than the localized

Beijing website for the two sections in question.

Table 31. Lexical Density of the Tourism Website Sections Available for Content-text

Comparison

Communicative Section L (%) NL (%) About Us 56.6 62.3 City Facts 63.4 64.2

Table 32 shows the average sentence length of the tourism website sections available for content-text comparison (L: Localized Beijing website; NL: Non-Localized DC website).

The localized Beijing website on average had longer sentences than the non-localized DC website for the two sections in question. It is noteworthy that the section “City Facts” for both websites featured much shorter sentences and a close look showed that the section “City

Facts” consisted of short phrases and sentences with attention-grabbing numbers.

Table 32. The Average Sentence Length of the Tourism Website Sections Available for

Content-text Comparison

Communicative Section L NL About Us 25.2 21.5 City Facts 10.4 8.7

Table 33 shows the relative frequency of first- and second-person sentences in the

government website sections available for content-text comparison (L: Localized Beijing website; NL: Non-Localized DC website). Both sections in question were dominated by a different type of voice for both websites.

Table 33. The Relative Frequency of First- and Second-person Sentences in the Government

Website Sections Available for Content-text Comparison

Communicative Section L (%) NL (%) About Us 85 0 City Facts 0 76

4.1.6 Cross-industry comparison.

As a summary of the paired comparison of localized and non-localized websites from five industry sectors in Sections 4.1.1-4.1.5, Table 34 lists all the conclusions drawn from the paired analysis of ten websites so as to inform the cross-industry comparison. Taking into account the practical limitation that the paired comparison within each industry dealt with different sets of website sections and not a single website section was shared by all five industry sectors under analysis, we can make the following hypotheses to be tested in the grouped comparison at Step 2 of Phase 1:

H1: Non-localized websites generally see a consistent comparison result with localized

websites in terms of the quantifiable textual features for the comparable content-text

sections under analysis, except for average sentence length, the paired comparison result

of which is inconclusive.

H2: The word count of the navigational text for a certain website section ranges between

1 and 5, and falls between 1 and 3 in most cases.

H3: University websites, localized or non-localized, feature the briefest and most

standardized navigational text of all five industry sectors, thus taking on a most detached

tone, which is illustrated by no or weak presence of first- and second-person voice.

H4: More localized than non-localized websites feature standalone “Home” navigation,

regardless of industry sector.

H5: Three types of non-localized organization websites, university, municipal

government, and tourism destination, group the communicative sections of potential

interest for different audiences, whereas no similar strategy of targeted communication

can be found in either the other two types of non-localized websites (LSP and

ecommerce) or most localized websites under study.

These hypotheses will be further tested on a larger dataset at Step 2 of Phase 1.

Table 34. Summary of Paired Comparison

Ecommerce Municipal Tourism Industry LSP University Feature Company Government Destination Avg. Wordcount L

Standardization of Industries and (5 standardized Recommended Help N/A Section Titles Technology sections in total) Activities and Events breadcrumb trail (L) " Home" N/A (both) N/A (both) Yes (L) vs. N/A (NL) Yes (L) vs. N/A (NL) vs. N/A (NL) Current and International students International Current and International travellers prospective clients, and scholars, faculty, travellers (L) vs. prospective buyers and temporary Suggested Target job seekers, visitors and alumni (L) vs. travellers, meeting (L) vs. buyers, residents (L) vs. Local Navigational Audience(s) interested in industry students, parents, planners, travel sellers, and job residents, visitors, and updates, and media and faculty and staff agencies, media, and Text seekers (NL) job seekers (NL) (both) (NL) job seekers (NL)

Sections about the Sections related to city's services to Technology- international research international visitors facilitated sections collaboration and IPR (L) vs. local residents, Travel tips & Code of ethics (L) vs. and IPR (L ) vs. Distinct Sections (L) vs. advising & travellers, educators, travelogue (L) vs. technology (NL) culture-oriented tutoring and job seekers, and visitors careers & deals (NL) sections and Sellers undergraduate reseach interested in updates on (NL) (NL) public administration (NL) Lexical Density LNL LNL LNL Length Content Text Percentage of 1st & (Very high for both L 2nd Person L

4.2 Step 2 of Phase 1: Grouped Comparison

In this step of analysis, localized and non-localized websites from four industry

sectors, LSP, university, government, and tourism destination, were grouped in eight sets of

nine websites selected from each industry sector (see Appendix A for the list of websites

under analysis). Ecommerce was excluded from the current analysis due to the unavailability

of localized English ecommerce websites. Each group of localized websites was first

compared with its non-localized counterpart from the same industry sector with respect to the

five textual features as specified in Table 3, and a cross-industry comparison was conducted

after the within-industry comparisons. Regardless of industry sector, the localized and non-

localized groups were all compared for the commonly shared sections that have been

identified in the within-industry paired comparisons at Step 1 of Phase 1.

4.2.1 LSP.

This section studies a total of five different textual features of the comparable website

sections identified in the paired comparison of LSP websites (see Section 4.1.1 for the

sections shared by localized and non-localized LSP websites). All the sections were compared for one feature related to navigational text, while only one section, Company (Organization)

Profile, was studied for the other four features related to content text, because Company

(Organization) Profile was the only section shared by all the website samples under analysis.

Other commonly shared sections were found to involve more than two levels of webpages,

which is beyond the scope of the current study.

This comparison model was in turn applied to all the other three industry sectors

under analysis to facilitate the subsequent cross-industry comparison, while taking into

account the fact that different industry sectors do not share an identical set of comparable

sections.

Appendix B lists the lexical items fulfilling similar navigational purposes in the

localized and non-localized LSP websites (L: Localized group; NL: Non-Localized group).

When comparing the findings with the analysis of Table 5, it is interesting to note that a majority of the navigational text contained no more than three words and the only longer exceptions were page headings that are not clickable text links. Secondly, the section

Industries still saw a high level of standardization in the grouped comparison of LSP websites, whereas the section Technology was not highlighted in quite a few non-localized

LSP websites. However, another section, Contact Us, was found to be standardized in most localized and non-localized LSP websites under comparison, though this section was intended to fulfill purposes that vary from company to company. Some Contact Us sections were designed to invite the potential client’s request for quote, some to address any inquiries from interested parties, some to receive job applications, and some others to fulfill some or all of these functions. Thirdly, there was a sharp contrast between localized and non-localized

LSP websites in terms of the presence of “Home.” Eight out of the nine localized LSP websites had a “Home” button at the top of the homepage, whereas only three out of the nine non-localized counterparts featured “Home” navigation. Furthermore, two out of the three non-localized websites featuring “Home” navigation had no “Home” button on the homepage. Instead, “Home” was shown as a text link in the breadcrumb trail at the top of subpages. There was not much variation between localized and non-localized groups with respect to the presence of first- and second-person voice in navigational text; both groups saw

a relatively strong first- and second-person voice in such sections as Company Profile and

customers and job seekers, as suggested by their navigational texts.

Table 35 shows the other four features of content text for both groups (L: Localized

group; NL: Non-Localized group) and Figure 6 shows the word clouds for these two groups

(left: localized group; right: non-localized group).

The most frequent content words shared by both groups were Language, Quality,

Service, Solution, Company, and Translation. These words represent an industry mission of

LSP—providing quality language services and solutions, the prototypical form of which is

translation. On the other hand, one significant difference was that the localized LSP websites

mainly targeted Chinese markets and emphasized the technological expertise, while the non-

localized ones featured a global view and stressed the importance of team approach to

business development.

As for content text, unlike paired comparison, the non-localized group had lower

lexical density and shorter average sentence length than the localized group. However, the

presence of first- and second-person voice was stronger in the non-localized group, which is

consistent with the paired comparison.

Table 35. Four Features Related to Content Text for the Grouped Comparison of LSP

Websites

LSP L NL Localization Translation Language Service Global China Business The most frequent content Client Company Lexical L2 words (Percentage of Total Language Solution Analysis Words > 0.5%) Quality Service Technology Quality Company Team Solution Translation

L3 Lexical density 63.20% 62.00% S1 The mean sentence length 17.05 12.08 Sentential The relative frequency of first- Analysis S2 and second-person sentences 82% 88%

Figure 6. Word Clouds for the Two LSP Website Groups

4.2.2 University.

Appendix C lists the lexical items fulfilling similar navigational purposes in the localized and non-localized university websites (L: Localized group; NL: Non-Localized group). When comparing the findings with the analysis of Table 17, we can see that like the grouped comparison of LSP websites, the prevalence of one- and two-word lexical items has also been found in the navigational text of both university-website groups. Secondly, the localized group, like the non-localized group, showed a prominent level of standardization of

navigational text. The only variation across university that can be found in the sections under

comparison was the inclusion of university name, such as Life@MIT, Career at BNU, and so

on. Thirdly, like the paired comparison, the detachedness of overall voice can also be felt in

grouped comparison of university websites, as evidenced by a weak presence of first- and

second-person voice in the navigational text except for Contact Us and only a few instances

of About Us. Finally, five out of the nine localized university websites featured homepage

navigation, in two of which “Home” was shown as a clickable text link in the breadcrumb

trail, while only three of the non-localized university websites featured homepage navigation,

all embodied by “Home” shown in the breadcrumb trail.

Table 36 shows the other four features of content text for both university website

groups (L: Localized group; NL: Non-Localized group). The most frequent content words shared by both groups were University and Research, thus suggesting that university websites tend to promote the research expertise. The variation in frequent words showed that the localized university websites under study reflect a collectivist view and stress science-related activities as well as national support, while the non-localized university websites, similar to the non-localized LSP websites, hold a global view and take a people-oriented approach to supporting students and faculty.

As for content text, the results of lexical density were as inconclusive as the paired comparison. Furthermore, like the paired comparison, the localized university-website group had longer sentences on average and saw a much weaker presence of first- and second-person

voice than the non-localized group.

Table 36. Four Features Related to Content Text for the Grouped Comparison of University

Websites

University L NL

University Students The most frequent National University content words L2 Research World (Percentage of Total China Words > 0.5%) Research Lexical Analysis Education Faculty Science

L3 Lexical density 60.77% 60.27%

The mean sentence S1 length Sentential 25.66 11.43 Analysis The relative frequency S2 of first- and second- person sentences 7% 64% Figure 7 shows the word clouds for these two groups (left: localized group; right: non- localized group).

Figure 7. Word Clouds for the Two University Website Groups

4.2.3 Government.

Appendix D lists the lexical items fulfilling similar navigational purposes in the localized and non-localized government websites (L: Localized group; NL: Non-Localized

group). When comparing the findings with the analysis of Table 23, we can see that the word

count of navigational text for both groups also ranges from one to three. Similar to the group

comparison of university websites, the government websites see a weak presence of first- and second-person voice except for About Us and Contact Us in some instances. Lastly, all the localized government websites feature explicit homepage navigation in form of a “Home” button in the navigation bar at the top of the webpage. On the other hand, six out of the nine non-localized websites feature homepage navigation, two of which see “Home” as a clickable text link in the breadcrumb trail.

As can be seen from Appendix D, no section can provide an adequate textual basis for comparing the two groups of government websites. This can be attributable to the fact that most non-localized government websites are designed for online services and such an interactive service platform is quite different from the role played by most non-localized government websites as information platforms for providing references and consultation services. Therefore, no comparison was done for the content text of the two government- website groups in question due to unavailability of data.

4.2.4 Tourism destination.

Appendix E lists the lexical items fulfilling similar navigational purposes in the localized and non-localized tourism-destination websites (L: Localized group; NL: Non-

Localized group). When comparing the findings with the analysis of Table 29, we can see that similar to the paired comparison, the navigational text of both groups ranged from one to three words long and the word count of the navigational text for the non-localized websites was on average a little longer than that of the localized websites. Secondly, both groups saw

lexical standardization for three sections, “Recommended Activities,” “About Us,” and

“Events.” Thirdly, the major website sections of both groups were all dominated by third-

person voice. Lastly, the feature of explicit homepage navigation can be found in all of the

localized websites and none of the non-localized websites.

To compare the content text, it is noteworthy that only a few tourism-destination

websites under analysis shared a comparable section. The only section shared by most

websites was “About Us.” Nevertheless, the theme of this section varies from instance to

instance. There were altogether three themes that can be identified from these two groups of

tourism-destination websites under discussion. One was the profile of the organization

sponsoring the website (L1, L3, L4, L7, L8, NL1, NL2, NL3, NL6, NL7, and NL8), the

second was the profile of the website (L3, L6), and the last was the profile of the city the

website promotes (L2). Taking into account this variation in theme, Table 37 shows the other

four features of content text for the tourism-destination website groups (L: Localized group;

NL: Non-Localized group), focused only on the section About Us dealing with the first theme. The most frequent content words shared by both groups were Tourism, City, and

Travel, pointing to the industry sector the websites belong to. The variation in frequent words showed that the localized group promotes local tour packages, while the non-localized group works to develop the potential of the city serving as a convention destination in addition to a tourist attraction.

As for the other three features of content text, first of all, similar to the paired comparison, the non-localized group had higher lexical density than the localized group for the section in question. Also, consistent with the paired comparison, the localized group on

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average had longer sentences than the non-localized one. Lastly, the localized group saw a

stronger presence of first- and second-person voice than the non-localized group, again consistent with the paired comparison.

Table 37. Four Features Related to Content Text for the Grouped Comparison of Tourism-

destination Websites

Tourism Destination L NL Tourism San Francisco Industry Tourism Tibet Destination Beijing Travel City City The most frequent content Shanghai Marketing L2 words (Percentage of Total Municipal Visitor Lexical Analysis Words > 0.5%) Travel Convention International Orlando Service NYC Tour Business Guilin Company Local Organization L3 Lexical density 58.82% 62.94% S1 The mean sentence length 17.14 13.81 Sentential Analysis The relative frequency of first- S2 and second-person sentences 77% 72% Figure 8 shows the word clouds for these two groups (left: localized group; right: non-

localized group).

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Figure 8. Word Clouds for the Two Tourism-destination Website Groups

4.2.5 Cross-industry comparison.

As a summary of the grouped comparison of localized and non-localized websites

from four industry sectors in Sections 4.2.1-4.2.4, Table 38 shows the conclusions drawn

from the grouped analysis of 72 websites so as to inform the cross-industry comparison (L:

Localized group; NL: Non-Localized group).

Table 38. Summary of Grouped Comparison

Municipal Tourism LSP University Government Destination Explicit Homepage Navigational Text L(8) > NL(4) L(5) > NL(3) L(9) > NL(6) L(9) > NL(0) Navigation Lexical Density L>NL L>NL L>NL Avg. Sentence L>NL L>NL L>NL Content Text Length N/A 1st & 2nd Person LNL Point of View

Based on the results of grouped comparison, all the hypotheses formulated in Section

4.1.6 can be supported or not supported as follows:

1. The non-localized websites generally exhibit smaller measures of textual features

than the localized websites for the comparable section “About Us” under analysis,

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except for the presence of first- and second-person voice, in terms of which the

non-localized group is stronger than the localized group. Therefore, the hypothesis

H1 is not supported.

2. Regardless of group or industry, the word count of the navigational text for About

Us section ranges between 1 and 5, and falls between 1 and 3 in most cases.

Therefore, the hypothesis H2 is supported.

3. Like university websites, government websites in general feature a weak presence

of first- and second-person voice. Therefore, the hypothesis H3 is rejected.

4. More localized websites than non-localized websites feature explicit homepage

navigation, in particular LSP and tourism-destination websites. Therefore, the

hypothesis H4 is not supported.

5. Table 39 shows the comparison result of the presence of gateway feature for both

website groups (L: Localized group; NL: Non-Localized group). It can be seen

that more non-localized websites than localized websites feature separate

gateways for different audience types for three out of the four industry sectors

under analysis, while LSP websites, non-localized or localized, have no such

design. Therefore, the hypothesis H5 is supported in three industry sectors.

Table 39. The Presence of Gateway Feature

Municipal Tourism LSP University Government Destination N/A L(5) < NL(9) L(3) < NL(6) L(2) < NL(7)

Section 4.2 thus concludes the descriptive statistical analysis and Section 4.3 will test the statistical significance of feature-specific differences identified between the localized and

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non-localized website groups. Furthermore, Section 4.3 will also statistically explore whether

the selected features exhibited in website texts were influenced by the two independent

factors, source language and industry.

4.3 Phase 2: A Statistical Exploration of Industry- and Language-specific Effects

Based upon the premise that only texts from comparable website sections can be compared in the current study, only two types of organization websites, LSP and university, were involved in the current phase of inferential statistical analysis, since only these two featured a comparable section, About Us, for textual analysis. The other organization websites under analysis either lacked any comparable website section or featured a theme other than organization profile in their About Us sections. Thus, the independent variables studied in Phase 2 were Industry (with two levels, LSP and university) and Localization

Profile (with two levels as well, localized and non-localized). And the dependent variables in the inferential statistical analysis were three content-text features studied in both paired and grouped comparisons; these three features were (1) the average sentence length, (2) lexical density, and (3) the percentage of first- and second-person sentences.

The required sample size for performing the MANOVA test in Phase 2 was calculated by a specialized sample-size calculator, G*Power 3.1. The input and output parameters in the calculator are shown in Figure 9, with a medium effect size set at 0.0625, α at 0.05, and a power of 0.8 (Faul, Erdfelder, Lang, & Buchner, 2007). The number of levels of the predictor variable, Industry, is two instead of five for Phase 2—LSP and University, and the other predictor variable, Localization Profile, also has two levels, Localized (from Chinese) and

Non-localized (American English), so the input parameter of total group size is 2 × 2 = 4.

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And the number of outcome variables was set at 3 in correspondence to the three features related to content text under analysis. As G*Power shows, the required sample size for the current study is 88, which means that 22 website samples were selected for each group. Phase

2 needs a bigger than sample size than Phase 1 for the purpose of performing statistically meaningful tests.

Figure 9. Input Parameters and Output Calculation Results of G*Power

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Twenty-two China-based LSP websites were randomly selected from the list of

translation agencies in China on translationdirectory.com (2012a), a leading job site for translation services. And twenty-two US-based LSP websites were randomly selected from

the list of translation agencies in the United States on translationdirectory.com (2012b). As

for the selection of university websites, twenty-two China-based university websites were randomly selected from the list of top 100 Chinese universities on webometrics.info and twenty-two US-based university websites were randomly selected from the list of top 100

American universities on the same website. Appendix F shows a list of 88 websites thus selected for Phase 2. The textual data were extracted from the About Us section of these websites.

The content text of About Us from each website was then loaded into analyzemywriting.com and countwordsworth.com to calculate the three content-text features, the former site calculating lexical density while the latter average sentence length and percentage of first- and second-person sentences. Next, the calculation results were loaded into SPSS for multivariate data analysis.

Table 40 shows the descriptive statistical results of the four groups (LocProfile:

Localization Profile; AveSentLeng: Average Sentence Length; PercentPerson: Percentage of

First- and Second-person Sentences). It can be seen that regardless of industry sector, the means of localized groups were higher than their non-localized counterparts in terms of

average sentence length and the reverse was true with respect to the presence of first- and second-person voice, while no significant difference in lexical density was found between the localized and non-localized groups.

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Table 40. Descriptive Statistical Results

Table 41 shows the multivariate test results for the main effect and interaction effect of the two independent variables (LocProfile: Localization Profile). The fact that the significance of the four tests was all less than 0.05 points to a significant main effect of both independent variables and a significant interaction effect between them.

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Table 41. Multivariate Tests for the Independent Variables

Table 42 shows the tests of between-subject effects to explore the effect of source language and industry on each feature of content text (LocProfile: Localization Profile;

AveSentLeng: Average Sentence Length; PercentPerson: Percentage of First- and Second- person Sentences). It can be seen that lexical density was not significantly influenced by either source language or industry or even their interaction (sig. > 0.05), while the other two features, average sentence length and percentage of first- and second-person sentences, were significantly influenced by both independent variables, source language and industry, as well as the interaction between them (sig.= 0.00 < 0.05).

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Table 42. Tests of Between-subject Effects

As a visual presentation of the correlation between independent and dependent variables, Figure 10 shows the profile plots of the estimated marginal means of the three textual features in relation to industry for the localized and non-localized groups (from left to

right: average sentence length, lexical density, and percentage of first- and second-person

sentences). Since intersecting lines on the plot indicate a correlation, lexical density did not

see a correlation as strong as the other two features.

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Figure 10. Profile Plots

To sum up, there was a statistically significant interaction effect between industry and

source language on the combined content-text features as dependent variables, F(3, 82) =

8.812, p = .000; Wilks' Λ = .756. In respect to the content text of About Us section, the localized and non-localized groups, LSP or university, were significantly different from each other in terms of average sentence length and percentage of first- and second-person sentences, but no significant difference was found in terms of lexical density between the localized and non-localized groups.

Considering the limitation in sample size and the small number of comparable industry sectors under study, it would be premature at this stage to argue for the existence of an English variant. What can be argued for now is that English-language websites of some

Chinese organizations have exhibited textual-linguistic features that deviate from their non- localized counterparts of American organizations. It has yet to been seen whether the deviations as identified in the current study will find further prominence in future development of web-mediated communication.

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4.4 Summary

The current chapter presented and analyzed the results of both qualitative and quantitative results for applicable website sections, in particular the About Us section for performing statistical analysis. Both navigational and content text were comparatively studied for specific features on localized and non-localized websites. Section 4.1 dealt with the pairwise comparison of localized and non-localized websites from five industry sectors. Based upon the preliminary comparison results thus produced, Section 4.2 made a grouped comparison of localized and non-localized websites from four of the industry sectors to confirm or disapprove the findings in Section 4.1. Lastly, Section 4.3 ran an inferential statistical test on the textual features of localized and non-localized websites from two of the industry sectors,

LSP and university. The test illuminated the main effect and interaction effect of industry and localization profile on two of the textual features, average sentence length and presence of first- and second-person voice, combined and separately. The next chapter will discuss the originality of the current study, explore the limitations, and outline promising directions for further development of the current line of research.

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V. Discussion and Conclusion

The overall structure of the current chapter echoes that of Chapter 3 by reflecting upon the current study from three perspectives: instrument (Section 5.1), data (Section 5.2), and analytical framework (Section 5.3). The reflective analysis will review the research findings and consider the limitations so as to explore possible avenues for future studies.

Next, Section 5.4 envisions empirical studies of website texts, as illustrated by the current study, as a promising field for cross-fertilization of teaching, research, and industry practice.

Finally, Section 5.5 concludes the dissertation with a summary.

5.1 Instrument

The textual analysis of websites poses a demand for an integrated framework of data

processing and management which is built upon an in-depth appreciation of the complexity

of text and language. In the current study, the measurement tools of conventional texts were

applied individually to website texts which had been extracted from the specified webpages

and the webpages of interest were in turn downloaded from the websites under analysis.

Cross-platform operations like these negatively affect the efficiency of data analysis and

make it difficult to apply the instrument to a larger dataset of websites.

On the other hand, as for technical procedures, the researcher of website texts, unlike

that of conventional texts, not only needs to choose additional tools for converting website

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data into plain text, but also needs to remove undesirable textual noise from the extracted raw

text. The textual noise in the current study includes image alt (alternative) text6 and website section titles appearing repetitively for navigation across different levels of webpages.

At first sight, it was tempting to choose R over a set of tools for designing such a system to facilitate the lifecycle management of text data, since as a programming language known for statistical computing and graphics, R boasts an abundance of ready-made packages to fulfill different objectives of data collection, processing and analysis. If R had been found applicable to the current study, each and every task related to the text data under study would have been performed within R environment, resulting in an integrated system to deliver improved efficiency in data analysis. Nevertheless, a major technical challenge turned the researcher away from R for the current study.

The leading contributor to the difficulties in R programming for the current study is code adaptation. To extract the website text of interest, the R code needs to be revised and customized to accommodate the coding scheme of each and every organization website. Most websites under analysis were characterized by different HTML tag arrangements for the textual sections due to variations in design and formatting. This means that although it is feasible to adapt the R code to a certain website for a “noise-free” extraction of the texts of interest, this adaptation has to be done on a case-by-case basis, since websites seldom follow consistent text formatting, thus making it necessary to develop a one-fits-all code for delimiting the body text in the source code of any webpage. Hence, the current study relied

6 The alternative text, providing alternative information for an image, will be displayed in place of the image if a user for some reason cannot view the image on a website. 113

on the online web-text extractor for a full extraction of webpage texts and manually removed

textual noise from each webpage of text.

Another observation made about the differences between the processing of website texts and that of conventional texts is that the definitions of some textual features underlying

the algorithm of prevalent analysis tools call for reconsideration in the context of website

studies. One case in point is “sentence.” A sentence, as defined in a majority of tools, if not

all, is an orderly sequence of words ended with one of the three punctuation mark serving as a

terminal point, that is, a period, a question mark, or an exclamation mark. The sentence-level

calculation and analysis are totally dependent on this definition. This may not pose much of a

problem in the studies of conventional text, as each and every sentence is expected to be

ended with a terminal point. However, the website text adds to the complexity in addressing

the question of how to define a sentence. For instance, website writing favors brevity and

clarity, as a result, bulleted or numbered lists are regarded as a highly recommended way of

organizing and presenting information. To end each item in a list, most punctuation guides

specify that a punctuation mark needs to be put at an end of a sentence, but not a fragment or

a word. In reality, however, it can be found in the current study that the list items on most

websites under analysis were not ended with an applicable punctuation mark, sentence or not.

This approach has made a great impact on the results produced by conventional text-analysis

tools. To reconcile the tool algorithm with the website context, the researcher put an end mark

at the end of those sentence items when manually removing textual noise. This illustrates the

necessity of customized definitions of textual features and in turn a system of customized

tools for the analysis of website text.

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In spite of all the difficulties discussed here, the researcher firmly believes that an

integrated system that incorporates data collection, processing, and management is achievable

in the context of textual studies for websites. Along this line of thinking, future studies will

explore the operationalized definition of web-based textual features as well as the

categorization of coding scheme for website text formatting, to promote the design of an all-

in-one, R-based system for website text analysis. The importance of such a system lies in its high efficiency in analyzing large website datasets across industry and time. Furthermore, the online publication of this integrated system will promote the replicability of research

procedures and consequently contribute to a comprehensive understanding of web-mediated

organizational communication by rallying the efforts of researchers worldwide sharing

similar interests.

5.2 Data

To further expand on the topic of extended datasets in Section 5.1, this section outlines future research directions on studying varied, larger datasets by specifically discussing two types of website texts, navigational text (5.2.1) and content text (5.2.2), in line

with the multi-dimensional comparisons in Chapter 4. As can be seen from the current study,

the number of comparable websites and website sections saw a steady decrease across steps

and phases. This is mainly attributable to the pre-study restriction that only the first two levels of webpages from a website were analyzed for acquiring the first extensive view. In general, future studies will combine longitudinal and latitudinal comparisons by looking at more industries, more English-language websites localized from other languages, as well as

the evolution of website writing over time. In addition, future studies will involve automated

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tagging tools in pre-processing larger datasets. See the following two subsections for further

analysis of navigational text and content text, respectively.

5.2.1 Navigational text: The buttress of website convention.

One of the most important conventional features of organization websites is the navigational text in particular section titles, giving a brief description of the website sections in question. For conventionalized sections such as About Us, Contact Us, and News, website visitors have already had some idea of what to expect, or a “generic mental model,” as

described by Nielsen and Tahir (2012), before clicking on the text link. Just as a title

contributes to the arguments developed in the rest of the essay, so a section title identifies the

content text in the corresponding section. Therefore, for the analysis of navigational text, the

current study mainly focused on section titles representing navigational text due to their

prevalence across different levels of webpages as well as their close ties with content text.

Two types of sections can be identified from the comparisons: one is for characterizing

organization websites from different industries and can be named industry-specific website sections, and the other is for characterizing organization websites at large and can be named organization-specific website sections. Table 43 lists the industry- and organization-specific website sections identified in the current study. These sections were shared by most of the localized and non-localized websites in question.

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Table 43. The Industry- and Organization-specific Website Sections

Website Sections Industry-specific Organization-specific Industry Type What We Do (Services) Technology LSP Featured Client Solutions Industry Blogs and Resources Product Classification Deals Ecommerce Help About Us Call for Partners Contact Us Academics Join Us Admissions News and Events University Campus Life Legal Notices (e.g., privacy policy, Call for Donations terms and conditions of use, and Education disclaimer) Government Feedback FAQ Recommended Activities Accommodation Tourism Destination Routes and Tours Neighborhoods As shown in Table 43, the industry-specific website sections can suggest the industry type of a website; one can almost tell which industry a group of sections belong to by looking at the industry-specific sections alone. One noteworthy industry sector here is LSP, the industry-specific sections of which are very likely to overlap with other service-oriented industry sectors which are beyond the scope of the current study. In addition, the identified sections unique to the government website do not necessarily point to government-specific conventions, which mean that government websites have yet to see a noticeable level of conventionalization. On the other hand, organization-specific website sections can be viewed as the fundamental building blocks of an organization website and thus give some good pointers for content planning of an organization website, though it is noteworthy that the

About Us section may witness thematic variations in different organization websites. Future studies will conduct the within-industry analysis of industry-specific website sections on a larger dataset, trace how a certain section evolves over time, or carry out a cross-industry

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analysis of organization-specific website sections to involve more industries and

organizations.

There are also some textual features that can be operationalized for further studies.

Firstly, we can run a statistical test on the presence of homepage navigation cue, “Home,” for

a larger dataset; the MANOVA test also applies to categorical dependent variables. The same

applies to the presence of redundant links, which can be defined as a common feature of

organization website where links to important sections, located at the page top, usually

reappear in a different wording at the page bottom, so as to get a second chance of winning

the visitor’s attention. Lastly, the types of grammatical forms navigational texts take can also be explored in future studies, so at to inform the localization practice.

In respect to the actual wording of comparable website section titles, the localized and

non-localized websites under analysis did not see much difference in that non-localized

websites themselves saw a lot of variations in the title wording of many of the website

sections in question. It is not difficult to locate more than four ways of describing a website

section from the grouped comparison (see Appendices B-E). University is the industry sector

that has seen the highest level of navigational-text standardization. This in a way suggests

that though some website sections have seen conventionalization, the textual representation

for a website section varied from website to website, localized or non-localized. Future

qualitative analysis can continue to document different ways of describing a website section

and discuss the rationale for choosing one expression over another in a certain section based

on case studies.

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5.2.2 Content text: The emergence of convention.

Unlike the study of navigational text, where the quantitative analysis was conducted

with no prior reference due to a lack of extant literature, the features under analysis for content

text were all derived from the previous studies of Chinese-into-English website translation.

Two of the textual features, average sentence length and the presence of first- and second-

person voice, have seen statistically significant difference between localized and non-localized

website groups, especially for a few industries, including university. As no relevant literature

on this language pair for website localization and translation was found in the academic

publications outside China, future studies will expand the search for operationalized features

of website text to consult the literature on the comparison of translated and non-translated text

involving English. On the other hand, English-language websites of organizations based in countries where English is not the first language can be compared with their Chinese and

American counterparts in future studies. One source language under consideration is Japanese, which is believed to be close to Chinese language compared with Indo-European languages, and the other is French or German, which is supposed to be two major languages relatively close to English language according to the linguistic distance of European languages (Elms,

2008).

Another interesting research topic related to content text is the identification of characteristics of English variants. If the English-language websites of American organizations represent American English, what kind of English do the English-language websites of organizations based in non-English speaking countries represent? Based upon the feature

119

studies of global English varieties,7 future studies can evaluate worldwide English-language

organization websites and explore possible explanations.

5.3 Analytical Framework

Not only is it important to add nuance and sophistication to the current analytical

framework with more features to be studied as suggested in the prior two sections, it is also

essential for future studies to involve website users in website evaluation. User surveys and

focus groups can be planned and structured according to the empirical findings of website

products and the data of user studies can in turn inform product-oriented studies.

It is also necessary for future product-oriented studies to keep up with technology trends

by looking beyond computer-based websites. With the development of mobile applications and

targeted marketing, today’s organizations can also reach their potential clients with mobile-

friendly websites and newsletters. These forms of up-to-date communication are all noteworthy

research topics to feel the pulse of organizational discourse, though the “traditional” computer-

based website serves as a good starting point, since the mobile-based versions of organization

websites are mostly synopsis or excerpts of their computer-based versions. To quote Halvorson

and Rach (2012), “as evolving technology continues to throw us one curve ball after the next,

keeping a handle on our content—no matter where it is and who it’s for—has become more critical than ever.”

7 https://www.uni-due.de/SVE/

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5.4 From Content to Content Strategy: Website Analysis as a Booming Field of

Interdisciplinary Collaboration between Academia and Industry

Content, as defined by Halvorson and Rach (2012) from a business perspective, is the critical information the website, application, intranet, or any other delivery vehicle created to contain or communicate. Content creation is not an end in itself; following and practicing a unified content strategy is. Content strategy is what guides our plans for the creation, delivery, and governance of content (Halvorson & Rach, 2012). To have a content strategy in place calls for the collaboration of multiple or even all teams in an organization. The same applies to the context of organization website. Website content, in broad terms, can be defined as anything published on the website to help readers and business (Fenton & Lee,

2014). As language and visual-effect professionals, creators and editors of website content need to closely work with other organizational units, including but not limited to marketing, communication, IT, and user experience, to negotiate and reconcile the expectations and priorities of different stakeholders. Text and language should not be regarded as an afterthought in presenting corporate image on the Web. Instead, planning, implementing, and reviewing of content should be addressed as part of an ongoing improvement cycle of organizational communication.

With the increased attention to content and content strategy, we can expect more exciting opportunities of linking teaching and research as well as bridging the gap between academia and industry. For instance, students taking courses in web authoring and website localization can learn the general procedures and guidelines of content auditing (a quantitative and qualitative accounting of all currently published web content, with all the

121

details recorded in a spreadsheet; see Halvorson & Rach, 2012). Equipped with the

theoretical knowledge, they can then practice designing flows (a series of screens that walks

readers through a task; see Fenton & Lee, 2014), run user tests on real or fictional websites of

interest, and interview or read and discuss the interviews with industry practitioners to have a

clearer idea of theory in practice. By surveying working professionals about their varied

understanding of the organization they work for and the corporate image they strive at

achieving, students are involved in what Tiffani Jones Brown calls organizational

anthropological work (Fenton & Lee, 2014). Future classrooms can even anticipate the

engagement of both language and non-language major students, since textual and non-textual

features coexist and interact with one another on a website, which necessitates collaborative

learning of different disciplines. This echoes Kiraly’s (2000) socio-constructivist model. By practicing teamwork skills with authentic materials and situational projects (Gouadec, 2007), the students will learn to appreciate a practical view of content creation and development for the benefit of their career planning and future professional life. While contributing to the curriculum of web design and authoring with authentic materials and analysis results, the empirical findings of website localization products can be fed into the studies of Internet linguistics as well as the industry practice of website content development, which in turn inform the academic training and localization education. Such a virtuous cycle, as foretold by

Jiménez-Crespo (2013a, p. 186), can “provide the optimal framework for localization competence acquisition.”

Most works on content strategy, if not all, elude the multilingual aspect of content. As a professional working with two or more languages, localization and translation practitioners

122

can find new possibilities of career advancement in working together with other functional

teams in business to develop, implement, and review the content strategy of international

organizations. Content strategists are highly likely to become the next promising career

option for language-major and translation-major graduates following language project

managers.

5.5 Concluding Remarks

According to Dunne (2006), linguistic aspects of a website, similar to those of a software product, tend to be forgotten because functional aspects of the website can be objectively assessed and website localization are therefore perceived as processes akin to manufacturing. The current study counteracted this trend by specifically looking at text and language on the organization website, calling for attention to a wide range of textual, discursive, and communicative problems in web genres (Jiménez-Crespo, 2013a).

In all, the comparisons of localized and non-localized organization websites showed

remarkable differences in terms of some of the textual features under analysis. And some

characteristics exhibited by websites were found to be affected by industry and localization

profile. Yet, it would be hasty to conclude that localized or non-localized websites from an

industry are already conventionalized with regard to some textual-linguistic features. Taking into account the convenience sampling strategy the current study took, the researcher will strive at a more balanced sampling strategy in future studies.

It is also important to acknowledge that some of the selected localized websites, especially from such industries as university, government and tourism destination, need redesigning and restructuring compared with their non-localized counterparts. The current

123

study spotted the following common problems: links not working, English-version website

slow to load, and the naming of webpage file naming infeasible for regular retrievals and

updates. However, it would be cursory to dismiss non-localized websites as inferior to localized ones and to embrace without questioning the localization maxim that localized products should provide a native look and feel that will be accepted in a target region. There are two main rationales for applying critical thinking to website localization. First of all, not all localized website in the current study were themselves standardized or conventionalized in terms of textual features and titles of commonly shared sections. Therefore, it would be best for website localizers to choose one or multiple benchmark websites before carrying out user needs analysis on a case-by-case basis. Secondly, careful consideration should be given to removing from a localized website everything that is “non-native” or strange to the target market. One case in point is one of the most frequent content words found on localized websites of universities, governments, and tourism destination — “China.” In contrast, country names, including “the USA,” were rarely found on the websites of American organizations in the current study. Nevertheless, simply eliminating all instances of “China” from localized websites would only lose a unique competitive edge in promoting country-specific characteristics.

The current study proposed and implemented an analytical framework for the multi- dimensional comparison of localized and non-localized website texts, and combined quantitative and qualitative data analysis with descriptive and inferential statistical methods.

Built upon the current study and equipped with refined methodology, future studies will involve more industry sectors and apply textual extraction at a deeper level to contribute to a better

124

understanding of industry clusters and ultimately the universe of organizations as projected onto the cyberspace.

125

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APPENDICES

A. The Websites Selected for Grouped Comparisons at Step 2 of Phase 1 Localized (China) Non-localized (USA) LSP

L1-Pactera Technology Lionbridge L1 International NL1 (https://www.lionbridge.com/) (https://en.pactera.com/)

CSOFT International TransPerfect L2 NL2 (https://www.csoftintl.com/) (http://www.transperfect.com/)

FBC GLOBAL LanguageLine Solutions L3 (http://www.globalfbc.com/ NL3 (https://www.languageline.com/) ?lang=en)

EC Innovations, Inc. Welocalize, Inc. L4 (http://www.ecinnovations.c NL4 (https://www.welocalize.com/) om/en.html)

Lan-bridge CyraCom International, Inc. Communications L5 NL5 (http://www.cyracominternational.c (http://www.lan- om/) bridge.co.uk/)

WordTech International Donnelley Financial Solutions L6 (http://www.wordtechintl.c NL6 (http://www.donnelleylanguagesolut om/) ions.com/)

Master Translation Services United Language Group L7 NL7 (http://www.mts-tech.com/) (http://unitedlanguagegroup.com/)

LocaTran Translations Ltd. ManpowerGroup Solutions - L8 (http://www.locatran.com/e NL8 Language Services ng/index.asp) (http://www.mgslanguage.com/)

Sunyu CN L9 (http://www.sunyu.com/ind NL9 AKORBI (https://akorbi.com/) ex.asp)

142

University

Tsinghua University Massachusetts Institute of L1 (http://www.tsinghua.edu.cn NL1 Technology (MIT) (web.mit.edu/) /publish/newthuen/)

Peking University Stanford University L2 NL2 (english.pku.edu.cn/) (https://www.stanford.edu/)

Fudan University Harvard University L3 NL3 (www.fudan.edu.cn/en/) (https://www.harvard.edu/)

Shanghai Jiao Tong California Institute of Technology L4 NL4 University (en.sjtu.edu.cn/) (Caltech) (www.caltech.edu/)

Zhejiang University University of Chicago L5 NL5 (www.zju.edu.cn/english/) (https://www.uchicago.edu/)

University of Science and Princeton University L6 Technology of China NL6 (https://www.princeton.edu/) (en.ustc.edu.cn/)

Nanjing University Cornell University L7 (https://www.nju.edu.cn/E NL7 (https://www.cornell.edu/) N/)

Beijing Normal University Yale University L8 NL8 (english.bnu.edu.cn/) (https://www.yale.edu/)

Wuhan University Johns Hopkins University L9 NL9 (en.whu.edu.cn/) (https://www.jhu.edu)

143

Government Shanghai (http://www.shanghai.gov.c New York City, NY L1 NL1 n/shanghai/node27118/inde (http://www1.nyc.gov/) x.html)

Beijing Los Angeles, CA L2 (http://www.ebeijing.gov.cn NL2 (https://www.lacity.org/your- /) government)

Chicago, IL Guangzhou, Guangdong L3 NL3 (https://www.cityofchicago.org/city/ (english.gz.gov.cn/) en/chicagogovt.html)

Shenzhen, Guangdong Houston, TX L4 NL4 (english.sz.gov.cn/) (www.houstontx.gov/)

Wuhan, Hubei L5 NL5 Philadelphia, PA (www.phila.gov/) (english.wh.gov.cn/)

Dongguan, Guangdong Phoenix, AZ L6 (http://www.dongguantoday NL6 (https://www.phoenix.gov/citygover .com/) nment)

San Antonio, TX L7 Chongqing (en.cq.gov.cn/) NL7 (www.sanantonio.gov/)

Chengdu, Sichuan San Diego, CA L8 (http://www.chengdu.gov.c NL8 (https://www.sandiego.gov/) n/english/)

Dallas, TX Nanjing, Jiangsu L9 NL9 (dallascityhall.com/government/Pag (english.nanjing.gov.cn/) es/default.aspx)

144

Tourism Desitination

Beijing New York City, NY L1 (http://en.visitbeijing.com.cn NL1 (https://www.nycgo.com/) /)

Xi’an, Shaanxi Los Angeles, CA L2 (http://www.xian- NL2 (https://www.discoverlosangeles.co travel.com/) m/)

Shanghai (www.meet-in- Orlando, FL L3 NL3 shanghai.net/) (www.visitorlando.com/)

Guilin, Guangxi Las Vegas, NV L4 NL4 (http://www.visitguilin.org/) (https://www.visitlasvegas.com/)

Hangzhou, Zhejiang Chicago, IL L5 NL5 (http://en.gotohz.com/) (https://www.choosechicago.com/)

Chengdu, Sichuan Washington DC L6 NL6 (www.gochengdu.cn/) (https://washington.org/)

Huangshan, Anhui San Francisco, CA L7 (http://www.huangshantour. NL7 (www.sftravel.com/) com/english/)

Lhasa, Tibet Miami, FL L8 (http://www.tibetdiscovery. NL8 (www.miamiandbeaches.com/) com/lhasa-travel/)

Suzhou, Jiangsu Denver, CO L9 NL9 (en.visitsz.com/) (https://www.denver.org/)

145

B. The Lexical Items of Different Sections of LSP Websites (L: Localized website; NL: Non-Localized website)

146

C. The Lexical Items of Different Sections of University Websites (L: Localized website; NL: Non-Localized website)

Communicative Section L1 L2 L3 L4 L5 L6 L7 L8 L9 NL1 NL2 NL3 NL4 NL5 NL6 NL7 NL8 NL9

About Us About M eet About About PKU About Fudan About SJTU About About About About BNU About WHU About MIT About Harvard About Caltech About Princeton About Cornell About Yale About Us

Admissions Admission & Admissions & Admission & Admissions & Admissions Admission Admissions Admission Admissions Admissions Admissions Admission Admission Admission Admission Aid Admissionscade c Aid Aid Admissions Admissions Aid Divisions Academics & Academics & International (under Academics Research Research (Admissions) Academics Academicsy (Schools) Academics (Academics p Education Academics Schools Researchy & Academics Academics y; Academics Academics Academics Faculty Faculty Staff (under individual Staff (under Our Staff Faculty & Staff Administratio (under (under Working at Faculty & Faculty & subsites of Faculty and About (Faculty and (under Meet Faculty and Faculty and Research & Faculties n Admissions) Academics) the Faculty Staff Staff schools and N/A N/A Staff Caltech) Staff) Princeton) Staff Staff Faculty （under Academics & Academics & Research & Research & Research & Research Research Research Research Research Research Research Research Research Research Research Research N/A Education） Research Research Research Collections Faculty Campus Life Student Life Campus Life (under (under One Campus N/A Campus Life Life @ SJTU Campus Life Services Campus Life Campus Life Campus Life Life@M IT Campus Life On Campus Student) Campus Life Community) Student Life Life at Yale Campus Life

News University News & News & Uchicago Cornell News & News News News News News News News News Events News News Gazette News Events News News Chronicle News Events Resources Opportunity | Join Us (under Career at Join Us | Job Employment Jobs Employment N/A Join Us Working at Join Us Join Us BNU Careers Jobs Careers Jobs Careers Opportunities N/A N/A Opportunities N/A Contact Us Contact Us (under About Contact Contact the Contacts N/A Contact Us SJTU) Contact N/A Contact Us Contact Us Contact Us Contact Contact Harvard Contact Us Contact Us Contact Us Contact Contact Us University Give to MIT | Giving | Give | Call for Donations Giving to Giving to Giving (under Give | M ake a Giving to Support Give to the Giving to TH PKU Giving Giving (Alumni) N/A Give M ake a Gift N/A MIT Giving Give Alumni) Gift Princeton Cornell Giving University

Terms and Conditions of Use N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A Terms of Use N/A N/A N/A N/A N/A N/A N/A

Privacy Policy Privacy Privacy Privacy Privacy N/A N/A N/A N/A oN/A epage ( N/A N/A N/A N/A N/A Policy Statement Statement N/A N/A N/A Policy N/A the Home (in the Home (in the Home (in the Home (in the Home breadcrumb breadcrumb breadcrumb breadcrumb breadcrumb N/A N/A N/A Home trail) trail) N/A Home Home N/A N/A N/A N/A N/A N/A trail) trail) trail)

147

D. The Lexical Items of Different Sections of Government Websites (L: Localized website; NL: Non-Localized website)

Communicative Section L1 L2 L3 L4 L5 L6 L7 L8 L9 NL1 NL2 NL3 NL4 NL5 NL6 NL7 NL8 NL9

Education Schooling for Study in Education (under Education (under Study Study Education N/A Foreign Children N/A Chongqing Residents) Study Education N/A Education N/A Topics) N/A N/A Public Schools N/A welcome to M ESSAGE Welcome message www.shanghai.g Welcome to FROM THE ov.cn Welcome Speech N/A N/A N/A N/A Chongqing N/A N/A N/A N/A N/A N/A N/A CITY N/A N/A Official News Now | News (under News Releases & News & Events Our San Diego News | Spotlight News & Events Activities | City News & News and Other News | Office of the Other City (under Mayor's City News and and Explore San | Featured News | News Mayor's Bulletin What's On Local News Wuhan News Coming Events Official Release News News and Events Mayor); Events Public Notices Updates News and Events Office) Information City Spotlight Diego Public Notices Provide Feedback Feedback about Website Interact Feedback Guest Book Contact Us N/A N/A Feedback Feedback Contact Us NYC.gov Submit feedback Feedback Your Feedback N/A Contact Us Contact Us Contact the City Feedback (designed for (designed for (designed for (designed for Frequently FAQ individual individual individual individual Asked Questions FAQ Q&A Quick Links N/A N/A N/A FAQ N/A sections) sections) sections) sections) FAQs (under Report a N/A N/A N/A Contact Us

Privacy policy Services and Security & Privacy Policy & N/A Privacy N/A N/A N/A N/A Privacy Policy N/A N/A Privacy Policy Privacy Policy Privacy Policy Privacy Policy HIPAA Privacy Disclaimer Privacy Policy Privacy Policy

Terms and conditions of use Terms and Privacy Policy & N/A Copyright Disclaimer N/A N/A Legal Notice Conditions N/A Legal Declaration Terms of Use Disclaimer Disclaimer N/A Terms of Use N/A Disclaimer Disclaimers Disclaimer Home (icon in sa.gov (in the Home the breadcrumb breadcrumb trail Home Home Home Home Home Home Home Home Home Home (icon) N/A Home (icon) trail) Home (icon) N/A home) Home (icon) N/A

148

E. The Lexical Items of Different Sections of Tourism-destination Websites (L: Localized website; NL: Non-Localized website)

Communicative Section L1 L2 L3 L4 L5 L6 L7 L8 L9 NL1 NL2 NL3 NL4 NL5 NL6 NL7 NL8 NL9 Top Lhasa (Multiple Things to Do | Things to Do Highlights Sightseeing Things to Do Attractions N/A Attractions and See & Do What to Do Things to Do Things to Do Things to Do Things to Do Everything to Do Things to Do Things to Do Recommended Activities Sections) Explore Activities

Xian Hotels & Lhasa Hotels & Accommodation Hotels Accommodation Accommodations St ay Hotels Accommodations St ay Where to Stay Places to Stay Hotels & Casinos Hotels Places to Stay Hotels Where to Stay Hotels Accommodation Hostels Hostels

T hemed T ours | Suggest ed Season Tour in (Multiple Itineraries & Trip-planning Trip Ideas & T ours & T ours & Routes & Strategy N/A Tour Itineraries Rout es Rout es N/A N/A Trip Ideas Itineraries Routes and tours Special Tours Itineraries Chengdu Sections) Guides Ideas Itineraries Sightseeing Excursions

Other Denver China City Guide | Around Beijing N/A N/A N/A N/A N/A Destinations in N/A N/A Neighborhoods N/A N/A Neighborhoods Neighborhoods Neighborhoods N/A Neighborhood Neighborhoods Destinations T ibet Guide

Xian Getting to & Get t ing Around Get t ing Around Getting To & Transportation & Transportation Transportation Local Transport N/A Traffic Transportation (in an article) Transportation Getting Around Transportation Transportation Get Around Transportation Transportation around Lhasa Vegas DC Around Miami Maps

Festivals & Events This Events N/A Events Events Events N/A N/A N/A Events Events Shows & Events Events & Shows Events Events Events Events Events Events Month DC Insider Sign Up for Newsletter (for What's (Sign-up for News N/A Travel News Travel News E-Journals What's New News Center N/A What's New News & Trending Press Releases What's New E-Newsletter Press Room News Newsletter email Happening Newsletter) subscription) About Us / About About Us (homepage) About Us About N/A About About Us About Us N/A About Us About Us Abo ut LVCVA About Us About Abo ut GMCVB About Denver About Us Careers Desitnation DC

Contact Us (a Contact N/A About Us About (homepage) Contact Us E-mail Us Contact Us Contact Us (About Us) N/A Contact Us N/A Contact Us Contact Us (Abo ut GMCVB) N/A Contact Us link to email) Destination DC

Home (in the Home (in the Home (in the Home (in the Home (in the Home (in the Home Home N/A N/A N/A N/A N/A N/A N/A N/A N/A Home Home breadcrumb t rail) breadcrumb t rail) breadcrumb t rail) breadcrumb t rail) breadcrumb t rail) breadcrumb t rail)

149

F. The Websites Selected for Phase 2 (L: Localized; NL: Non-Localized)

Localized (China) Non-localized (USA) LSP University LSP University Indiana University/Purdue Xiamen Target Language Translation Northwest Agriculture and Forestry Bureaucom University, Indianapolis L1 Service Co. Ltd. University NL1 (http://www.bureaucom.com/) (https://www.iupui.edu/about/index. (http://www.language-trans.com/en/) (http://en.nwsuaf.edu.cn/) html)

Guangzhou Synergy Translations Co., Nanjing Medical University NetaRose New York University L2 Ltd., China NL2 (http://e-sie.njmu.edu.cn/) (http://www.netarose.com/) (https://www.nyu.edu/about.html) (http://www.synergytranslations.com/)

University of Science & Heron Language Services Linearis Translations North Carolina State University L3 Technology Beijing NL3 (http://www.heronlanguageservices (http://linearistranslations.com/) (http://www.ncsu.edu/) (http://en.ustb.edu.cn/) .com/) JiangSu LanguAge Information Shenzhen University EzeeTranslate University of California Riverside L4 Technology Services Co., Ltd. , China (http://www1.szu.edu.cn/2014/en/o NL4 (https://www.ezeetranslate.com/) (http://www.ucr.edu/about) (http://www.jslga.com/en/index.asp) verview.html) Shaanxi Normal University University of Miami LingoNova Accent Network L5 (http://english.snnu.edu.cn/About/In NL5 (https://welcome.miami.edu/about- (http://www.lingonova.com/) (http://www.accentnetwork.com) troduction_to_SNNU.htm) um/index.html) Nanjing University of Posts and Chengdu Refine Translation Co.,Ltd, Telecommunications U.S. Language Solutions University of Nebraska Lincoln L6 China NL6 (http://www.njupt.edu.cn/en/7873/li (http://uslsolutions.com/) (https://www.unl.edu/about/) (http://www.m3loc.com/) st.htm) Hohai University Transn BeTranslating Case Western Reserve University L7 (http://en.hhu.edu.cn/p402c343/list. NL7 (http://www.transn.com/) (https://betranslating.com/) (http://case.edu/) psp)

South China Agricultural University Universal Translation Studio 1 Stopasia, China University of Georgia L8 (http://english.scau.edu.cn/2016/122 NL8 (https://www.universaltranslationstu (https://www.1stopasia.com/) (http://www.uga.edu/about/) 7/c1169a30289/page.htm) dio.com/)

University of Chinese Academy of SY Localization Sciences Gateway Languages University of Cincinnati L9 NL9 (http://www.sylocalization.com/) (http://english.ucas.ac.cn/index.php/ (http://gatewaylanguages.com/) (http://www.uc.edu/) about-ucas/introduction)

Tnfast Translations University of Jinan University of Illinois Urbana Logrus IT L10 (http://tnfast.com/beijing-translation- (http://www.ujn.edu.cn/en/About_ NL10 Champaign (http://www.logrusit.com/) services/) UJN__/Introduction_to_UJN.htm) (http://illinois.edu/)

East China Normal University GMR Transcription Takeasy Translation App, China Oregon State University L11 (http://english.ecnu.edu.cn/1712/list. NL11 (https://www.gmrtranscription.com/ (https://www.itakeeasy.com) (http://oregonstate.edu/) htm) ) Taijia Translation Company Jiangsu University Verba++ Yale University L12 (http://www.taijiatrans.com/english/inde (http://eng.ujs.edu.cn/About_JSU/O NL12 (http://www.verbaplusplus.com/abo (http://www.yale.edu/) x.asp) verview.htm) ut.html) Hunan University Good Enterprise Limited (http://www- Primatus Northwestern University L13 (http://www.gel- NL13 en.hnu.edu.cn/About_HNU/Introdu (http://www.primatus.net/) (http://www.northwestern.edu/) global.com/web/common/index.asp) ction.htm) Star Translation Shanghai Nanjing Normal University We Translate Tufts University L14 (http://www.startranslation.com/index.h NL14 (http://en.njnu.edu.cn/about-nnu) (http://www.wetranslateinc.com/) (https://www.tufts.edu/) tm) Peking University Health Science ODB Translation Center Vanan Translation Purdue University L15 NL15 (http://www.odbfy.com/) (http://e.bjmu.edu.cn/aboutpkuhsc/g (https://vanantranslation.com/) (http://www.purdue.edu/) eneralinformation/index.htm)

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