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Researchers continue to address the concept of self-disclosure because it is foundational for helping social networking sites (SNS) function and thrive. Nevertheless, the authors' literature review indicates that uncertainty remains around the underlying mechanisms and factors involved in the self-disclosure process. The purpose of this research is to better understand the self-disclosure process from the lens of dual-process theory (DPT). The authors consider both the controlled factors (i.e. self-presentation and reciprocity) and an automatic factor (i.e. social influence to use an SNS) involved in self-disclosure and broaden The authors proposed a model to include the interactive facets of enjoyment.

The proposed model was empirically validated by conducting a survey among users of WeChat Moments in China.

As hypothesized, this research confirms that enjoyment and automatic processing (i.e. social influence to use an SNS) are complementary in the SNS self-disclosure process and enjoyment negatively moderates the positive relationship between controlled factor (i.e. self-presentation) and self-disclosure.

Theoretically, this study offers a new perspective on explaining SNS self-disclosure by adopting DPT. Specifically, this study contributes to the extant SNS research by applying DPT to examine how the controlled factors and the automatic factor shape self-disclosure processes and how enjoyment influences vary across these processes – enriching knowledge about SNS self-disclosure behaviors. Practically, the authors provide important design guidelines to practitioners concerning devising mechanisms to foster more automatic-enjoyable value-added functions to improve SNS users' participation and engagement.

The purpose of this paper is to review intuition in the context of organizational change. The authors argue that intuition as a concept requires attention and its formulation is necessary prior to its application in organizations. The paper provides a critique of dual process theory and highlights shortcomings in organization theorizing of intuition.

The paper is conceptual and provides in-depth theoretical discussions by drawing from the literature on decision and intuition in the context of organizational change.

Investigating whether dual process theory is sufficiently clear, the authors found ambiguity. Specifically, the current definition provided by Dane and Pratt is not clear in terms of its four sections: the consciousness of non-conscious processing, involving holistic associations, that are produced rapidly, which result in affectively charged judgments. Finally, the authors note that the evolutionary perspective is missing and they provide foundational concepts for such a perspective, including the discussion of information templates, memes and genes, as argued by research, condition intuition.

The paper finds that an evolutionary perspective develops a picture of intuition as an adaptive resource. This evolutionary perspective is currently absent in research and the authors provide foundational concepts for such a perspective. They propose specific arguments to highlight the evolutionary perspective.

With the proliferation of ideas submitted by users in firm-built online user innovation communities, community managers are faced with the problem of user idea overload. The purpose of this paper is to explore the influencing factors on the idea adoption to identify high quality ideas, and then propose a method to quickly filter high value ideas.

The authors collected more than 110,000 data submitted by Xiaomi community users and analyzed the factors affecting idea adoption using a multinomial logistic regression model. In addition, the authors also used BP neural network to predict the idea adoption process.

The empirical results show that idea semantics, number of likes, number of comments, number of related posts, the existence of pictures and self-presentation have positive impact on idea adoption, while idea length and idea timeliness had negative impact on idea adoption. In addition, this paper calculates the idea evaluation value through the idea adoption process predicted by neural network and the mean value of idea term frequency inverse document frequency (TF-IDF).

This empirical study expands the theoretical perspective of idea adoption research by using dual-process theory and enriches the research methods in the field of idea adoption research through the multinomial logistic regression method. Based on our findings, firms can quickly identify valuable ideas and effectively alleviate the information overload problem of online user innovation communities.

The purpose of this paper is to examine the push and pull factors associated with the consumption of Chinese Table Tennis Super League (CTTSL) game events by online audiences and on-site attendants.

Conducting a comprehensive review of literature and a test of content validity, a questionnaire was formulated to assess push and pull motives, event consumption, and sociodemographic variables. A total of 433 CTTSL event consumers, including 225 respondents who primarily followed CTTSL game events via television and webcasting and 208 respondents who primarily consumed the events by attending live game events.

Structural equation modeling analyses revealed that for online consumers, two push factors, self-esteem and drama excitement, were found to be positively related to the event consumption factors; whereas, social interaction and sport performance factors were found to be negatively predictive of event consumption factors. For on-site consumers, none of the push and pull factors were found to be related to the consumption factors.

These results indicate that unlike research findings derived in other research settings mainly conducted in Western countries, push and pull factors are more functional for online CTTSL consumers who are of comparatively stronger fandom level, which are likely affected by CTTSL’s contemporary operations.

Enriching the dual process theory through examining its applicability in studying sport consumer behavior, from both perspectives of internal and external motivations; applying theories and research findings of internal and external motivations that have primarily been derived in Western countries into a professional sport setting in China; identifying unique and diverse perspectives of professional table tennis consumers in China between online and on-site consumers; contrary to the findings derived in Western countries, the motivational factors are more functional for online CTTSL consumers who are of comparatively stronger fandom level, which are likely affected by CTTSL’s contemporary operations; and conducting micro-perspective analyses to study Chinese sport consumer behaviors, which has rarely been done in contemporary scholarly inquiries in China.

Despite the plethora of research into country-of-origin (COO) effects, research that investigates the cognitive structures behind elite consumers' preferences for foreign brands remains limited. Hence, this study aims to investigate the cognitive structures behind foreign brand preference among professional elites in Sri Lanka.

Using the means-end chain (MEC) theory as the theoretical lens and building on the findings of 30 laddering interviews (semi-structured), a survey was conducted among 311 professional elites to uncover the key elements of the cognitive structures behind foreign brand preference.

The findings revealed that the cognitive structures behind foreign brand preference are influenced by a bundle of brand attributes, brand consequences and personal values of elites', which significantly influence their attitudes towards foreign brands. Multi-group analysis further revealed that the relationship between brand attributes and attitudes significantly differs across Chinese and US COOs where the path coefficient is stronger for elites' preference for Chinese brands.

This study is the first of its kind to explore the COO effects on consumer cognitive structures. The findings contribute to MEC theory and shed light on the understanding towards elites' preference for foreign brands.

Expert evaluation is the backbone of the multi-criteria decision-making (MCDM) techniques. The experts make pairwise comparisons between criteria or alternatives in this evaluation. The mainstream research focus on the ambiguity in this process and use fuzzy logic. On the other hand, cognitive biases are the other but scarcely studied challenges to make accurate decisions. The purpose of this paper is to propose pilot filters – as a debiasing strategy – embedded in the MCDM techniques to reduce the effects of framing effect, loss aversion and status quo-type cognitive biases. The applicability of the proposed methodology is shown with analytic hierarchy process-based Technique for Order-Preference by Similarity to Ideal Solution method through a sustainable supplier selection problem.

The first filter's aim is to reduce framing bias with restructuring the questions. To manipulate the weights of criteria according to the degree of expected status quo and loss aversion biases is the second filter's aim. The second filter is implemented to a sustainable supplier selection problem.

The comparison of the results of biased and debiased ranking indicates that the best and worst suppliers did not change, but the ranking of suppliers changed. As a result, it is shown that, to obtain more accurate results, employing debiasing strategies is beneficial.

To the best of the author's knowledge, this approach is a novel way to cope with the cognitive biases. Applying this methodology easily to other MCDM techniques will help the decision makers to take more accurate decisions.

Drawing on the elaboration likelihood model (ELM), the authors examine the influence of perceived professor teaching qualities, as central cues, on online professor ratings. Also, our study investigates how the volume and period of reviews, as peripheral cues, affect online professor ratings.

Leveraging stratified random sampling, the authors collect reviews of 892 Information Systems professors from 250 American universities. The authors employ regression models while conducting robustness tests through multi-level logistic regression and causal inference methods.

Our results suggest that the central route from perceived professor qualities to online professor ratings is significant, including most qualitative pedagogical factors except positive assessment. In addition to course difficulty, the effect of the peripheral route is limited due to deficient diagnosticity.

Our primary concern about the data validity is a lack of a competing and complementary dataset. However, an institutional evaluation survey or an experimental study can corroborate our findings in future research.

Online professor review sites can enhance their perceived diagnosticity and credibility by increasing review vividness and promoting site interactivity. In addition to traditional institutional evaluations, professors can obtain insightful feedback from review sites to improve their teaching effectiveness.

To our best knowledge, this study is the first attempt to employ the ELM and accessibility-diagnosticity theory in explicating the information processing of online professor reviews. It also sheds light on various determinants and routes to persuasion, thus providing a novel theoretical perspective on online professor reviews.