Search results

With the prevalence of user-generated content on the internet, this study aims to propose a cognitive-affective-conative model to examine how users create and share their content online. The moderating role of gender differences is also tested in the model.

This study collects a representative sample of 873 internet users via a nation-wide survey in Taiwan.

The results show that hedonic value has a positive impact on internet satisfaction, and social value affects life satisfaction and internet satisfaction positively. Both life satisfaction and internet satisfaction are positively related to content sharing on the internet. In particular, the positive effect of life satisfaction on online content sharing is greater for male users than for female users.

This study contributes to the existing literature by investigating online content sharing behavior from the cognitive-affective-conative perspective. This study also provides a better understanding of this behavior by simultaneously examining life satisfaction and internet satisfaction as two underlying mechanisms. Furthermore, gender differences play an important role in determining content sharing on the internet.

For digital marketing practitioners, this study suggests several online editing and social mechanisms for encouraging users' engagement in content sharing behavior on the internet.

This study is one of the first that examines a cognitive-affective-conative framework of content sharing behavior on the internet. This study also demonstrates boundary conditions of this framework by testing the moderating role of gender differences.

To understand the effectiveness of electronic word of mouth, the purpose of this paper is to examine how high- vs low-knowledge consumers judge and attribute the credibility of positive and negative online reviews by drawing upon accessibility–diagnosticity theory and attribution theory.

This study conducts an observation-based study in an online forum and a 2 (review valence) × 2 (consumer knowledge) between-participants factorial experiment to examine the proposed hypotheses.

High-knowledge consumers elicit less perceived credibility and make more non-product-relevant attribution than low-knowledge consumers in negative online reviews. Consumer attribution is also found to mediate the effects of the review valence by consumer knowledge interaction on review credibility.

This study adds to extant research by examining how consumer knowledge plays a key role in determining consumer perception of online review credibility. This study also advances the understanding of different casual inferences about online reviews between high- and low-knowledge consumers.

The purpose of this paper is to investigate the effect of original equipment manufacturing (OEM) suppliers’ electronic integration with global customers on their capability widening, following the literature on electronic integration, firm innovativeness, product modularity and dynamic capabilities. It also examines the moderating roles of supplier innovativeness and product modularity in the proposed relationship.

This study conducts empirical examination on a sample of OEM suppliers in Taiwan. It collects 201 self-reported responses via mailed surveys of 1,069 electronics companies listed in the 5000 Largest Firms in Taiwan, and the archival data are obtained from the Taiwan Economic Journal database.

The results show that electronic integration with global customers affects capability widening negatively, whereas supplier innovativeness affects capability widening positively. In addition, product modularity plays a moderating role in the relationship between electronic integration and capability widening.

This study contributes to the electronic integration literature by providing empirical evidences on how OEM suppliers’ electronic integration affects their capability widening. This study also adds to the supply chain management literature by demonstrating the relationship between OEM suppliers’ innovativeness and their move into higher value-added activities, as well as how product modularity interplays with electronic integration between customers and suppliers on suppliers’ capability widening in global supplier‒customer relationships.

For OEM suppliers with a low level of product modularity, they may widen their capabilities by exploring other value-added activities (e.g. original design manufacturing or original brand manufacturing). For OEM suppliers with a high level of product modularity, the improvement of their manufacturing capabilities is a helpful approach to create competitive advantage.

This study is one of the first to examine the interplay between electronic integration and product modularity on capability widening of OEM suppliers from an emerging market. Meanwhile, this study provides support for the relationship between supplier innovativeness and innovative activities in the global supply chain context.

To improve the effectiveness of online reviews in the cultural industries, the purpose of this paper is to examine the effects of online cultural reviews of professional and consumer commentators on consumer responses toward elite and mass cultural offerings by drawing upon associative learning theory and social influence theory.

This study used a 2 (cultural offerings: elite vs mass)×2 (commentators: professional vs consumer) between-participants factorial design to examine the proposed hypotheses. A total of 195 participants were randomly assigned to one of four experimental cells.

The ANOVA results indicate that the credibility of online cultural reviews is significantly higher for professional commentators than for consumer commentators across both elite and mass cultural offerings. Furthermore, the results confirm that there is a significant cultural offering type by commentator interaction on a consumer's offering evaluation, overall attitude, and behavioral intention.

This study provides strong support for the congruence between cultural commentators and cultural offerings in online cultural reviews. The findings can also effectively explain the weak correlation between professional judgments and popular appeal.

For better effectiveness of online cultural reviews, the findings recommend cultural marketers that the use of professional commentators is effective for elite cultural offerings, whereas the use of consumer commentators is effective for mass cultural offerings.

This study proposes a useful dichotomy to classify cultural offerings as elite and mass. Meanwhile, this study is one of the first to examine the congruence between cultural offerings and cultural commentators in online reviews.

Panel data provide the possibilities of estimating individual treatment effects for multiple individuals. Two issues are considered: (1) differences in the estimated individual treatment effects are due to heterogeneity or a chance mechanism? (2) what is the best way to estimate the average treatment effects? Testing and aggregation methods are suggested. Monte Carlo simulations are also conducted to shed light on these two issues. An empirical analysis on the involvement of underground organization in China’s Peer-to-Peer (P2P) activities through the “anti-gang” campaign is also provided.

This chapter proposes semiparametric estimation of the relationship between growth rate of GDP per capita, growth rates of physical and human capital, labor as well as other covariates and common trends for a panel of 23 OECD countries observed over the period 1971–2015. The observed differentiated behaviors by country reveal strong heterogeneity. This is the motivation behind using a mixed fixed- and random coefficients model to estimate this relationship. In particular, this chapter uses a semiparametric specification with random intercepts and slopes coefficients. Motivated by Lee and Wand (2016), the authors estimate a mean field variational Bayes semiparametric model with random coefficients for this panel of countries. Results reveal nonparametric specifications for the common trends. The use of this flexible methodology may enrich the empirical growth literature underlining a large diversity of responses across variables and countries.

It is shown in the literature that the Arellano–Bond type generalized method of moments (GMM) of dynamic panel models is asymptotically biased (e.g., Hsiao & Zhang, 2015; Hsiao & Zhou, 2017). To correct the asymptotical bias of Arellano–Bond GMM, the authors suggest to use the jackknife instrumental variables estimation (JIVE) and also show that the JIVE of Arellano–Bond GMM is indeed asymptotically unbiased. Monte Carlo studies are conducted to compare the performance of the JIVE as well as Arellano–Bond GMM for linear dynamic panels. The authors demonstrate that the reliability of statistical inference depends critically on whether an estimator is asymptotically unbiased or not.

This paper provides a selective survey of the panel macroeconometric techniques that focus on controlling the impact of “unobserved heterogeneity” across individuals and over time to obtain valid inference for “structures” that are common across individuals and over time. We consider issues of (i) estimating vector autoregressive models; (ii) testing of unit root or cointegration; (iii) statistical inference for dynamic simultaneous equations models; (iv) policy evaluation; and (v) aggregation and prediction.

The purpose of this study is to propose an integrated model based on expectation–confirmation model (ECM), flow theory and human–organization–technology fit framework to examine whether human, organizational and technology factors as antecedents to medical professionals' beliefs can affect their continuance intention of the cloud-based e-learning system.

Sample data for this study were collected from medical professionals at five hospitals in Taiwan. A total of 500 questionnaires were distributed, and 368 (73.6%) useable questionnaires were analyzed using structural equation modeling in this study.

Synthetically speaking, human, organizational and technology factors, as antecedents to medical professionals' continuance intention of the cloud-based e-learning system have been examined, and the results strongly support the research model with all hypothesized links being significant.

Particularly, it is worth mentioning that the application of capturing both ECM and flow theory for completely explaining three types of factors (i.e. human, organizational and technology factors) as external variables to medical professionals' cloud-based e-learning continuance intention is well documented, that is, information systems (IS) and nonIS determinants are simultaneously evaluated, and extrinsic and intrinsic motivators are both taken into consideration in this study's theoretical development of medical professionals' cloud-based e-learning continuance intention to acquire a more comprehensive and robust analysis.