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Social media has emerged as a prominent platform for marketers and brands to disseminate brand-related information. This study aims to investigate the impact of color congruence between themes and background on marketing effectiveness, focusing specifically on Instagram.

A laboratory experiment was conducted to investigate how color congruence between themes and background in brand posts influences flow and aesthetic experience, subsequently affecting marketing communication parameters such as brand attitude, visit intention, and eWOM on Instagram. Moreover, Adidas Originals was selected as the focal brand, and blue and white color was chosen as the primary color palette for the experimental material.

This study demonstrates that color congruence, regardless of brand layout or post, significantly influences flow and aesthetic experience, subsequently affecting marketing effectiveness.

This study contributes to the theoretical understanding of congruence theory and social media marketing, providing valuable insights for brands to enhance their communication through photographs and effectively manage their official Instagram accounts.

Social media have become famous platform to search and share the COVID-19-related information. The objective of this research is to bridge the gap by proposing the effects of network cluster and transmitter activity on information sharing process.

Data were collected by using Facebook application, which was available for 14 days (May 1–14) in 2020. These data were analyzed to determine the influence of the network cluster and transmitter activity.

The results showed that network cluster is positively related to transmitter activity on social media. In addition, transmitter activity partially mediated the effect of network cluster on the extent of information liked and shared. That is, transmitter activity can affect COVID-19-related information sharing on Facebook, and the activity effect is plausible and should become stronger as social network become denser.

This study has contributed to the knowledge of health information sharing in social media and has generated new opportunities for research into the role of network cluster. As social media is firmly entrenched in society, researches that improve the experience or quality for users is potentially impactful.

The use of gamification might offer a partial solution to the decline in students' motivation and engagement the school system is currently facing. However, there has been a lack of empirical evidence on whether and how gamification may be able to improve learning motivation. Specifically, this study aims at exploring the antecedents and consequences of intrinsic learning motivation and its mediating role in gamification context.

A survey method was used to gather the information from students, and regression analysis was used to examine the relationship between three categories of gamification features (social, achievement and immersion), and intrinsic learning motivation. Moreover, this study further used self-determination theory to clarify how students' psychological needs (relatedness, competence and autonomy) mediate the effects of gamification and learning motivation.

Results showed that social, achievement and immersion features are key aspects that impact students' intrinsic motivation. The psychological needs of students can further enhance these relationships.

Overall, the findings illuminate the unique motivations for learning and reveal design strategies that can be implemented to improve teaching through gamification features.

Considering both online and offline service scenarios, this study aims to explore the factors affecting doctors' intention to offer consulting services in eHealth and compare the factors between the free- and paid-service doctors. The theory of reasoned action and social exchange theory are integrated to develop the research model that conceptualizes the role of extrinsic motivations, intrinsic motivations, costs, and attitudes in doctors' behavioral intentions.

Partial least square structural equation modeling (PLS-SEM) was leveraged to analyze 326 valid sample data. To provide robust results, three non-parametric multigroup analysis (MGA) methods, including the PLS-MGA, confidence set, and permutation test approaches, were applied to detect the potential heterogeneity between the free- and paid-service doctors.

The results with overall samples reveal that anticipated rewards, anticipated associations, anticipated contribution, and perceived fee are all positively related to attitude, which in turn positively influences behavioral intention, and that perceived fee positively moderates the relationship between attitude and behavioral intention. Attitude's full mediation is also confirmed. However, results vary between the two groups of doctors. The three MGA approaches return relatively convergent results, indicating that the effects of anticipated associations and perceived fee on attitude are significantly larger for the paid-service doctors, while that of anticipated rewards is found to be significantly larger for the free-service doctors.

eHealth, as a potential contactless alternative to face-to-face diagnoses, has recently attracted widespread attention, especially during the continued spread of COVID-19. Most existing studies have neglected the underlying heterogeneity between free- and paid-service doctors regarding their motivations to engage in online healthcare activities. This study advances the understanding of doctors' participation in eHealth by emphasizing their motivations derived from both online and offline service scenarios and comparing the differences between free- and paid-service doctors. Besides, horizontally comparing the results by applying diverse MGA approaches enriches empirical evidence for the selection of MGA approaches in PLS-SEM.

Recently, smart retail technology has emerged as an innovative technology that can improve consumer motivation and behavior in smart stores. Although prior studies have investigated factors influencing the adoption of smart retail technology, to the authors’ knowledge, no previous work has investigated the determinants of purchase intentions. The ultimate goal for retailers should be shopping, not technology adoption. However, traditional brick-and-mortar stores and theories focus on investing in utilitarian factors to attract customers. This study proposes that hedonic motivation should also play an important role, as new technologies may arouse customer curiosity and increase pleasant experiences. Therefore, the purpose of this study is to explore utilitarian and hedonic motivations that promote customers' purchase; intentions in smart stores. Specifically, the authors address the research questions: (1) What are the constituents of utilitarian motivation? (2) What are the constituents of hedonic motivation? (3) What are the factors that influence customers' purchase intentions? By answering the questions, the findings help retailers understand how to motivate customers to make purchases in smart stores.

To investigate consumer motivation and purchase intentions, the customers who made purchases in smart stores were invited to participate in the questionnaire survey. This study collected 307 data in smart retail settings. Partial least squares (PLS) software was used to assess the reliability, validity and the paths and significance of all hypotheses.

The results show that perceived ease of use directly and indirectly influences purchase intentions through utilitarian and hedonic motivations. Utilitarian motivation is a formative second-order construct comprised of merchandise price, merchandise quality, location convenience, speed of shopping and product recommendation. Hedonic motivation is a reflective second-order construct composed of control, curiosity, joy, focused immersion and temporal dissociation. The findings provide insights into the successful implementation of smart retail technology and offer retailers to better understand consumer motivation and purchase intentions in smart stores.

This study is the first to examine how consumer motivation influences purchase intentions in smart stores. This study posits and verifies the extended hedonic system acceptance model (HSAM) to explain consumer motivation for shopping in smart retail settings. This study also models the original first-order utilitarian and hedonic constructs as second-order formative and reflective constructs, respectively. Utilitarian motivation regarding functional benefits is developed based on the 5Ps of marketing and situational factors, while hedonic motivation regarding pleasant experiences is proposed based on cognitive absorption.

This research aims to investigate how entrepreneurial orientation influences a firm’s differentiation–cost advantage ambidexterity (DCAA) and performance indirectly through dynamic capabilities, while also investigating the impact of the interactive effect of the level and consistency of entrepreneurial orientation on dynamic capabilities. The goal of this study is to better understand the importance of consistently following an entrepreneurial orientation, as well as the linkage of such a consistently implemented strategy upon gaining both a cost and differentiation positioning enhancement.

Two empirical studies are conducted to test the proposed hypotheses – one longitudinal with multiple forms of data (i.e. text data, survey data and archival data) from 100 Taiwanese electronics firms and the other using primary data from a survey of senior managers.

Entrepreneurial orientation improves dynamic capabilities, which in turn promote superior DCAA and enhanced firm performance. In addition, as captured through a unique measure of consistency allowed through computer-aided text analysis, the results indicate that the effect of entrepreneurial orientation on dynamic capabilities is amplified when a firm consistently adopts entrepreneurial decisions and actions.

The specific context was a sample of electronics firms in Taiwan. This limits the generalization of findings, as would be possible with assessing the hypotheses in other industries.

This research clearly demonstrates the significance of consistency in pursuing a strategic orientation. The consistent support and deployment of resources facilitates an organization’s achieving positive outcomes associated with an entrepreneurial orientation.

While entrepreneurial orientation contributes to firm performance, extant knowledge on the internal process through which entrepreneurial orientation affects performance is relatively limited. The findings not only highlight the full mediating role of dynamic capabilities and DCAA, but also shed light on the importance of consistency in entrepreneurial orientation over time.

The purpose of this paper is to investigate switching intention from traditional enterprise information systems (EISs) to private cloud EIS in large enterprises. The authors propose that the factors motivate and inhibit enterprises’ switching intention to private EIS by integrating technology–organization–environment (TOE) framework and two-factor theory.

A research model draws from TOE framework and two-factor theory. Data were collected from 227 top managers and owners of the enterprises in China and used to analyze 11 hypotheses.

The results show that the technological context (compatibility), organizational context (financial support) and environmental context (vendor support and industry pressure) significantly influence switching benefits while data security and costs significantly influence switching costs. Switching benefits and switching costs significantly influence switching intention.

Past studies have focused mainly on the adoption of cloud computing. However, few studies have addressed the switching issues, especially in large enterprises. The findings are useful to understand switching issues from traditional EIS to private cloud EIS for both researchers and practitioners.

This study focuses primarily on the business operating departments (hereinafter, DMUs) of a case telecom company (hereinafter, the Company) in the northern and eastern areas of Taiwan. In 2007, the Company finished the first stage of its reorganization by consolidating 14 DMUs into 12. In 2011, the Company completed the second stage of its reorganization by consolidating the 12 remaining DMUs into 8. This study intends to explore the effects of each stage of the Company’s reorganization on the efficiency and ranking of the various DMUs. The results show that the DMUs became more efficient after each stage of the Company’s reorganization. Moreover, the efficiency and ranking of the new DMUs, A6, A7, and B7 increased post-consolidation. This suggests that both the first and second stages of the reorganization were necessary. The findings of this study could help the Company and other telecom companies to design strategies for the future consolidation of other units, and thereby maintain their competitiveness and continued growth.