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Resilience while learning is the capacity to initiate, persist and direct effort toward learning when experiencing unpleasant affective states. The underlying mechanisms of resilience are emotional buffering and self-regulation when experiencing unpleasant affective states. The authors identified four factors that support resilience while learning: positive emotional engagement, creative problem-solving, learning identity and social support. The authors developed and tested scales and found evidence to support the four-factor model of resilience. The authors offer a person-centered approach to resilience in learning by conducting a latent profile analysis that tested the likelihood of resilience based on profiles of differences in scores on these factors under two affective conditions: (unpleasant) learning during frustration versus (pleasant) learning during progress. A quarter of individuals activated the four resilience factors in pleasant and unpleasant affective states, while 75% of participants saw decrements in these factors when faced with frustration. The results support a four-factor, person-centered approach to resilience while learning.

The authors develop and test a four-factor model of resilience and test the model in a group of 330 management undergraduate and graduate students. Each participant identified two learning episodes in their responses, one while frustrated and one while making progress, and ranked the level of intensity on the four resilience factors. Analysis on an additional 88 subjects provided additional support for the validation and reliability of scales.

Results revealed 2 latent profiles groups, with 25% of the sample associated with resilience (low difference on resilience factors between the two learning episodes) and 75% who remain susceptible to unpleasant emotions (high difference between the two learning episodes).

The study supports a person-centered approach to resilience while learning (in contrast to a variable centered approach).

The study provides a means to classify individuals using a person-centered, rather than a variable-centered approach. An understanding of how individuals buffer and self-regulate while experiencing unpleasant affect while learning can help educators, consultants and managers develop better interventions for learning.

This study addresses the growing concern over student success associated with increased dropout rates among undergraduate business students, and the failure of many management developments and executive training efforts. This study suggests that looking at specific variables may not provide insight into the complex relationship between learning outcomes and factors that support resilience in learning.

There is growing interest in understanding resilience factors from a person-centered perspective using analytical methods such as latent profile analysis. This is the first study to look at how individuals can be grouped into similar profiles based on four resilience factors.

As independent travel has become increasingly popular in recent years, factors influencing users’ attitudes and behaviors should be explored. Besides, the rise of video platforms like YouTube, Bilibili and TikTok has led to the flourishing of user generated content (UGC), among which travel vlogs have become convenient and essential references for tourists before and while they travel on their own.

This research used quantitative analysis through a survey designed for young people, as most vlog viewers are in those age groups, to explore the attitudes and perceptions of vlog preference, attitudes and cognizance of travel vlogs among different gender, guided by the decision-making theory and preference theory with 455 participants.

Survey results showed that both genders have common choices regarding travel vlog preference, attitudes, sharing and cognizance. Yet, gender differences appear in some cognition of travel vlogs and specific preferences, such as information searching habits, trusty travel and information sources.

Existing studies focus on the influence of platforms on users, but scant studies focus on user perceptions of vlogs as a new information carrier for young people in East Asia, especially regarding gender differences, which is crucial in media-based marketing. This research provides practical suggestions to marketers and vloggers to attract and engage different genders of young people and theoretical implications on decision and preference theories.

Factor investment is booming in global asset management, especially environmental, social, and governance (ESG), dividend yield, and volatility factors. In this chapter, we use data from the US securities market from 2003 to 2019 to predict dividends and volatility factors through machine learning and historical data–based methods. After that, we utilize particle swarm optimization to construct the Markowitz portfolio with limits on the number of assets and weight restrictions. The empirical results show that that the prediction ability using XGBoost is superior to the historical factor investment method. Moreover, the investment performance of our portfolio with ESG, high-yield, and low-volatility factors outperforms baseline methods, especially the S&P 500 ETF.

Recent years have witnessed the popularity of social free sampling (SFS). That is, firms on social commerce platforms (e.g. Amazon Vine and Pconline Try) offer free sample products for consumers' applications, and the selected applicants are required to write a product trial report on the sites as a return. The main advantage of SFS is to leverage users' product trial reports to increase product exposure and attract prospective consumers. Thus, product trial reports play a central role in SFS. Despite that scholars have examined the rating bias of product trial reports in recent years' knowledge concerning how product trial reports influence user (i.e. readers of product trial reports) engagement remains sparse. To address the research gap, this paper aims to examine the drivers of user engagement with product trial reports.

This study utilized the Poisson regression model to analyze 3,419 trial reports collected from a well-known Chinese SFS site.

Based on the ELM model, the empirical results indicate that product rating, vividness, opinion balance, and reputation of the trial user are positively associated with user engagement. However, longer reports and reports with higher emotional intensity lead to weaker user engagement. Furthermore, product prices strengthen the positive impact of opinion balance but weaken the positive impact of trial users' reputations.

This study is among one of the first studies to investigate the impact of trial reports on user engagement in SFS. It yields actionable guidelines for SFS campaigns.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

To minimize customer churn, many service providers offer consumers the option of automatic contract renewal at the end of a contract period. Such agreements are known as rollover service contracts (RSCs). This research quantifies the effect of RSCs and other related factors, such as incentives, on consumers' service choice decisions.

The study adopts choice-based conjoint analysis to assess the effect of RSCs on consumers' choices and to determine whether effect size varies when selecting a cell phone network or gym/leisure club provider, which represent lower-priced utilitarian and higher-priced hedonic services.

It was found that RSCs produce negative perceptions and intended behaviors for the majority of consumers across different product types. Nevertheless, as explained by social exchange theory, many individuals may be persuaded to enter into a RSC on the basis of reciprocity if they are offered an incentive such as a price discount or free product add-on.

In the marketing domain, this is the first comprehensive study to quantify the role of contract type among a range of other factors in consumers' decision-making when selecting a service. The authors' results offer context-specific implications for service marketers. First, RSCs are perceived more negatively in high-priced hedonistic categories, especially among those with lower incomes. Second, price discounts are more effective than product add-ons for motivating hedonic purchases, while product add-ons work better with utilitarian services.

Why is it that highly trained and seasoned executives fail? On the surface, this doesn’t make sense because they are very successful; yet research in the organization sciences provides no shortage of evidence to prove just that. From the classic Mann Gulch fire disaster of Weick’s famous collapse of sensemaking study, to studies of myopia of learning, escalation of commitment, threat-rigidity, dominant logic, the architecture of simplicity, the Icarus Paradox, to core competencies turning into core rigidities, and navigating new competitive markets using “old” cognitive maps, and many more such examples point to a ubiquitous phenomenon where highly trained and experienced professionals find themselves “stuck” in the heat of battle, unable to move and progress. On the one hand, for some, there is a desperate need for change, but are unable to do so, due to their trained incapacities. On the other hand, some simply cannot see the need for change, and continue with their “business as usual” mentality. For both, their visions of the world shrink, they have a tendency to cling onto their past habitual practices and oversimplify the complexity of the situation. In moments like these: DROP YOUR TOOLS and UNLEARN! This book chapter introduces a framework (grounded in clinical psychology) that has had consistent success in helping seasoned executives and key decision-makers open up the alternatives whenever they find themselves stuck with complexity.

This conceptual, multi-voiced paper aims to collectively explore and theorize family entrepreneuring, which is a research stream dedicated to investigating the emergence and becoming of entrepreneurial phenomena in business families and family firms.

Because of the novelty of this research stream, the authors asked 20 scholars in entrepreneurship and family business to reflect on topics, methods and issues that should be addressed to move this field forward.

Authors highlight key challenges and point to new research directions for understanding family entrepreneuring in relation to issues such as agency, processualism and context.

This study offers a compilation of multiple perspectives and leverage recent developments in the fields of entrepreneurship and family business to advance research on family entrepreneuring.

This paper aims to investigate the influence of human resource management (HRM) practices on the level of innovativeness observed within the service sector of Ghana, taking into account the potential mediating role of innovation capability.

The research used a quantitative methodology to fulfill the study's objectives. A Web-based survey questionnaire was designed to gather data from a sample of 168 respondents, selected through a convenient sampling technique. The proposed model was tested using the Process Macro Model 4 by Hayes in SPSS version 26.

The study’s outcomes indicate that there is no statistically significant correlation between HRM practices and firm innovativeness. However, the mediating role of innovation capability was observed to fully account for the relationship between human HRM practices and firm innovativeness. Additionally, a positive and significant association was identified between HRM practices and innovation capability, as well as between innovation capability and firm innovativeness.

It is important to note that the findings are limited to the perspective of employees within the service sector of Ghana. Therefore, future research could explore the manufacturing and/or extraction industries in Ghana to obtain a more comprehensive understanding. Furthermore, a larger sample size could be considered in future studies.

To the best of the authors’ knowledge, this study presents a novel examination of the hypothesized model within the Ghanaian context, providing valuable insights into the relationship between HRM practices, innovation capability and firm innovativeness.

Purpose: The study aims to explore the wider acceptance of blockchain technology and growing faith in this technology among all business domains to mitigate the chances of fraud in various sectors.

Design/Methodology/Approach: The authors focus on studies conducted during 2015–2022 using keywords such as blockchain, fraud detection and financial domain for Systematic Literature Review (SLR). The SLR approach entails two databases, namely, Scopus and IEEE Xplore, to seek relevant articles covering the effectiveness of blockchain technology in controlling financial fraud.

Findings: The findings of the research explored different types of business domains using blockchains in detecting fraud. They examined their effectiveness in other sectors such as insurance, banks, online transactions, real estate, credit card usage, etc.

Practical Implications: The results of this research highlight (1) the real-life applications of blockchain technology to secure the gateway for online transactions; (2) people from diverse backgrounds with different business objectives can strongly rely on blockchains to prevent fraud.

Originality/Value: The SLR conducted in this study assists in the identification of future avenues with practical implications, making researchers aware of the work so far carried out for checking the effectiveness of blockchain; however, it does not ignore the possibility of zero to less effectiveness in some businesses which is yet to be explored.