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An automatic text annotation system (ATAS) that can collect resources from different databases through Linked Data (LD) for automatically annotating ancient texts was developed in this study to support digital humanities research. It allows the humanists referring to resources from diverse databases when interpreting ancient texts as well as provides a friendly text annotation reader for humanists interpreting ancient text through reading. The paper aims to discuss whether the ATAS is helpful to support digital humanities research or not.

Based on the quasi-experimental design, the ATAS developed in this study and MARKUS semi-ATAS were compared whether the significant differences in the reading effectiveness and technology acceptance for supporting humanists interpreting ancient text of the Ming dynasty’s collections existed or not. Additionally, lag sequential analysis was also used to analyze users’ operation behaviors on the ATAS. A semi-structured in-depth interview was also applied to understand users’ opinions and perception of using the ATAS to interpret ancient texts through reading.

The experimental results reveal that the ATAS has higher reading effectiveness than MARKUS semi-ATAS, but not reaching the statistically significant difference. The technology acceptance of the ATAS is significantly higher than that of MARKUS semi-ATAS. Particularly, the function comparison of the two systems shows that the ATAS presents more perceived ease of use on the functions of term search, connection to source websites and adding annotation than MARKUS semi-ATAS. Furthermore, the reading interface of ATAS is simple and understandable and is more suitable for reading than MARKUS semi-ATAS. Among all the considered LD sources, Moedict, which is an online Chinese dictionary, was confirmed as the most helpful one.

This study adopted Jieba Chinese parser to perform the word segmentation process based on a parser lexicon for the Chinese ancient texts of the Ming dynasty’s collections. The accuracy of word segmentation to a lexicon-based Chinese parser is limited due to ignoring the grammar and semantics of ancient texts. Moreover, the original parser lexicon used in Jieba Chinese parser only contains the modern words. This will reduce the accuracy of word segmentation for Chinese ancient texts. The two limitations that affect Jieba Chinese parser to correctly perform the word segmentation process for Chinese ancient texts will significantly affect the effectiveness of using ATAS to support digital humanities research. This study thus proposed a practicable scheme by adding new terms into the parser lexicon based on humanists’ self-judgment to improve the accuracy of word segmentation of Jieba Chinese parser.

Although some digital humanities platforms have been successfully developed to support digital humanities research for humanists, most of them have still not provided a friendly digital reading environment to support humanists on interpreting texts. For this reason, this study developed an ATAS that can automatically retrieve LD sources from different databases on the Internet to supply rich annotation information on reading texts to help humanists interpret texts. This study brings digital humanities research to a new ground.

This study proposed a novel ATAS that can automatically annotate useful information on an ancient text to increase the readability of the ancient text based on LD sources from different databases, thus helping humanists obtain a deeper and broader understanding in the ancient text. Currently, there is no this kind of tool developed for humanists to support digital humanities research.

In prior literature, online endorsement system allowing the users to “like” or “dislike” shared information is found very useful in information filtering and trust elicitation in most social networks. This paper shows that such systems could fail in the context of investment communities due to several psychological biases.

This study develops a series of regression analyses to model the “like”/“dislike” voting process and whether or not such endorsement distinguishes between valuable information and noise. Trading simulations are also used to validate the practical implications of the findings.

The main findings of this research are twofold: (1) in the context of investment communities, online endorsement system fails to signify value-relevant information and (2) bullish information and “wisdom over the past event” information receive more “likes” and fewer “dislikes” on average, but they underperform in stock market price discovery.

This study demonstrates that biased endorsement may lead to the failure of the online endorsement system as information gatekeeper in investment communities. Two underlying mechanisms are proposed and tested. This study opens up new research opportunities to investigate the causes of biased endorsement in online environment and motivates the development of alternative information filtering systems.

The study explores the mechanism between employee demand–ability fit and promotability ratings. Moreover, we examine whether political skill moderates the relationship above.

The present study received 260 effective supervisor-rated questionnaires from various industries in Taiwan.

The results reveal that employee demand–ability fit positively relates to promotability ratings, and task performance mediates the above relationship. In addition, political skill positively moderates the relationship between employee demand–ability fit and task performance.

We used the supervisor rating for our variables to test the hypotheses.

Digital humanities aim to use a digital-based revolutionary new way to carry out enhanced forms of humanities research more effectively and efficiently. This study develops a character social network relationship map tool (CSNRMT) that can semi-automatically assist digital humanists through human-computer interaction to more efficiently and accurately explore the character social network relationships from Chinese ancient texts for useful research findings.

With a counterbalanced design, semi-structured in-depth interview, and lag sequential analysis, a total of 21 research subjects participated in an experiment to examine the system effectiveness and technology acceptance of adopting the ancient book digital humanities research platform with and without the CSNRMT to interpret the characters and character social network relationships.

The experimental results reveal that the experimental group with the CSNRMT support appears higher system effectiveness on the interpretation of characters and character social network relationships than the control group without the CSNRMT, but does not achieve a statistically significant difference. Encouragingly, the experimental group with the CSNRMT support presents remarkably higher technology acceptance than the control group without the CSNRMT. Furthermore, use behaviors analyzed by lag sequential analysis reveal that the CSNRMT could assist digital humanists in the interpretation of character social network relationships. The results of the interview present positive opinions on the integration of system interface, smoothness of operation, and external search function.

Currently, the system effectiveness of exploring the character social network relationships from texts for useful research findings by using the CSNRMT developed in this study will be significantly affected by the accuracy of recognizing character names and character social network relationships from Chinese ancient texts. The developed CSNRMT will be more practical when the offered information about character names and character social network relationships is more accurate and broad.

This study develops an ancient book digital humanities research platform with an emerging CSNRMT that provides an easy-to-use real-time interaction interface to semi-automatically support digital humanists to perform digital humanities research with the need of exploring character social network relationships.

At present, a real-time social network analysis tool to provide a friendly interaction interface and effectively assist digital humanists in the digital humanities research with character social networks analysis is still lacked. This study thus presents the CSNRMT that can semi-automatically identify character names from Chinese ancient texts and provide an easy-to-use real-time interaction interface for supporting digital humanities research so that digital humanists could more efficiently and accurately establish character social network relationships from the analyzed texts to explore complicated character social networks relationship and find out useful research findings.

This study aims to empirically investigate how knowledge paradox affects collaboration performance. Knowledge paradox, which arises from the simultaneous need for knowledge sharing and protection, is common in interorganizational collaboration. Using the ambidexterity perspective, this paper aims to reexamine the effect of the knowledge paradox on collaborative performance to explore the moderating roles of structural and contextual ambidexterity.

This study used a sample of 153 firms involved in vertical and horizontal collaboration, collected via questionnaires. Hypotheses were tested using hierarchical regression analysis.

This study demonstrates that the stronger the knowledge paradox is, the higher the potential for value creation. Thus, knowledge paradox has a positive impact on collaborative performance. The functions of structural ambidexterity and contextual ambidexterity strengthen this positive relationship.

This paper not only expands the theoretical application of the knowledge paradox and ambidexterity theory in the context of interorganizational relationships but also provides significant managerial implications. By comprehending the dynamics of the knowledge paradox and the role of ambidexterity, managers can make well-informed decisions to enhance their collaborative performance.

Previous research has shown that consumers prefer a bonus pack to a price discount for virtue foods, whereas they prefer a price discount to a bonus pack for vice foods. Acting as a guilt-mitigating mechanism, a price discount justifies consumers' purchasing behavior, allowing them to save money and consume less vice foods. However, for virtue foods, neither the anticipated post-consumption guilt nor the resulting need for justification lead consumers to prefer a bonus pack to a price discount. This study investigates whether product promotions remain effective with other moderating variables.

The authors use pricing tactic persuasion knowledge (PTPK), which refers to the consumer persuasion knowledge of marketers' pricing tactics, as a lens to understand whether the power of these promotions could be enhanced or mitigated. The authors inferred that increasing the frequency of exposure to these foods could positively influence consumers' purchasing choices. They conducted three studies to examine these effects. In Study 1, using pearl milk tea (vice food) and sugar-free tea (virtue food), the authors contended that consumers would prefer a price discount when purchasing pearl milk tea, but a bonus pack when purchasing sugar-free tea. In Studies 2 and 3, the authors varied the participants' frequency of exposure to photographs of people in everyday situations with vice (virtue) foods.

In Study 1, PTPK was shown to be more predictive of consumer choices regarding price discounts and bonus packs. In Studies 2 and 3, the authors contended that increased exposure to vice (virtue) foods increases the selection of vice (virtue) foods by participants who were unaware of having been exposed to vice (virtue) foods.

This research has not only made quite managerial and policy implications for marketing but also brought the theoretical contributions for marketing researches. This research demonstrates that either for vice foods or virtue foods, a price discount is preferred to a bonus pack.

The purpose of this paper is to measure the influence of corruption distance (CD) on foreign direct investment (FDI) with the characteristics of the value function from the Prospect Theory (PT) such as loss aversion and diminishing sensitivity.

Data are derived from Transparency International and the Organisation for Economic Co-operation and Development (OECD) and tested on the countries China, Germany, Italy, Japan, Korea, Russia, Spain and the UK and are analysed with a natural log (LN) regression model.

The findings indicate a negative asymmetric relationship for China, Germany, Korea, Spain and Russia. This means that negative performance on CD will not have greater impact on FDI outflows than positive performance on CD in the same country. Loss aversion, as well as diminishing sensitivity, as suggested by the PT, cannot be supported with the empirical results.

Its originality lies in contributing and extending knowledge on CD on FDI in several ways. First, it analyses the data of emerging and industrialized countries, namely, Russia, China, Germany, Italy, Japan, Korea, Spain and the UK. Second, a potential asymmetric impact is explained by the characteristics of the hypothetical value function of the PT. Third, it seeks empirical evidence by applying an econometric model developed to analyse the variables CD and FDI.

The international marketing field has witnessed many studies related to “country of origin” (COO) effects or the “made in” concept over the past few decades. Yet COO research is deeply rooted in the so-called “production-related” approach, which mainly accounts for production- or technology-based factors. Barely considered is the “consumption-related” perspective, which reflects consumers' proclivity to base their buying decisions on foreigners' product choice. In this paper, we propose the “country of reference” (COR) concept, in which consumers deliberately imitate the product choices of consumers from another country, to whom the former (i.e. the imitators) attribute superior or more prestigious personas.

Unlike the made in concept, which emphasizes favored product qualities from superior manufacturing countries, we believe product preferences may arise from cross-border benchmarking or “cross-country referencing.” Pivoting on the optimal distinctiveness theory, this paper suggests a COR framework that incorporates the system justification theory and the self-discrepancy concept, along with decision heuristics and mental simulation effects. The proposed framework aims to explain consumers' inclination to “buy what certain foreigners buy.”

We suggest critical propositions related to the COR concept, discuss its marketing implications, and pinpoint further research issues.

COR may become a coping strategy through which low-status consumers perceiving themselves as less privileged than their high-status counterparts can narrow this gap by means of decision mimicking.

This study aims to develop an assessment scale for university service quality (university SQ) and examine University Service Quality assessment model (UNIQUAL) of higher education during the pandemic.

Two studies applied a mixed-method design to develop and validate the UNIQUAL scale. In-depth interviews and literature reviews were conducted to refine the initial dimensions and items of UNIQUAL in Study 1. Item analysis, EFA and CFA were then conducted to purify item refinement, scale refinement, purification and validation in Study 2. Finally, a confirmed UNIQUAL model was analyzed via partial least squares structural equation modeling (PLS-SEM) using Smart-PLS 4.0.

The research confirms the four-factor structure of UNIQUAL, with a total of 16 items, to be a valid and reliable scale for the assessment of the service quality (SQ) of universities. Having adopted the bias-corrected and accelerated (BCa) bootstrap approach to study 5,000 subsamples from 27 countries, the authors found “responsiveness” and “empathy” to be significantly associated and have positive relationships with students' satisfaction with university SQ. Furthermore, university SQ and satisfaction were mediated by “health and safety” concerns.

The newly developed UNIQUAL scale would be of value to educators and authorities of higher education to assess the SQ of their universities to enhance the effectiveness of student learning. The improvement in satisfaction with higher education's SQ ultimately helps in retaining both international and local students amidst concerns about traveling and studying during the pandemic.

COVID-19 has affected the private and public sectors worldwide. Millions of students have been affected by schools being shut down and substituted with distance-learning programs. Thus, the assessment of the quality of university services has become an important support mechanism for retaining the sustainability of higher education.

The UNIQUAL scale provides a conceptual model and validates an assessment tool. The research hypotheses confirm the relationship between university SQ and satisfaction from the perspective of international students.

Based on the social exchange theory, this study aims to investigate the influence of green supplier development (GSD) on supplier green innovativeness (SGI), the mediating role of buyer–supplier cooperation and the moderating role of preferred customer status (PCS).

This study uses stratified regression analysis to test the hypothesized relationships with data collected from 385 Chinese high-tech manufacturing enterprises.

The results of regression analysis show that GSD has a significant positive effect on buyer–supplier cooperation and SGI; buyer–supplier cooperation plays a partially mediating role between GSD and SGI; PCS strengthens the positive relationship between buyer–supplier cooperation and SGI and enhances the mediating role of buyer–supplier cooperation between GSD and SGI.

Supplier participation in green innovation is of great significance to the green development transformation of China’s manufacturing industry. This study reveals the positive impact of GSD on enhancing SGI and provides specific suggestions for manufacturing enterprises to realize efficient supplier management and build mutually beneficial and win-win cooperative relationships.

This study enriches and expands the related research on SGI antecedents and reveals the mediating mechanism and boundary conditions therein, which better makes up for the lack of attention to GSD in the existing research on supplier management and can provide lessons and references for the subsequent related researches targeting the enhancement and utilization of SGI.