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This study aims to contribute novel insights into understanding and mitigating the harmful consequences of abusive supervision (AS) by examining the association between AS experiences, revenge, forgiveness, and the moderating role of emotional intelligence (EI). The key argument is that employees' EI can influence the AS experience through affective processes, countering supervisors' abusive behaviors.

A between-person scenario-based experiment was conducted with 366 participants divided into AS and control groups. The study explored the association between AS experience and revenge/forgiveness, mediated by core affect (valence and activation). EI abilities were measured as a moderator. Data analysis examined the relationships and interactions among AS, revenge/forgiveness, EI, and affective experiences.

The study reveals significant findings indicating that AS experiences were positively associated with revenge and negatively associated with forgiveness. The mediation analysis confirmed the role of core affect in these relationships. EI emerged as a moderator, shaping the association between AS experiences and revenge/forgiveness. Importantly, participants with higher EI exhibited lower revenge intentions, demonstrating the potential of EI to mitigate the adverse effects of AS. Unexpectedly, individuals with high EI also expressed fewer forgiveness intentions.

This study provides a comprehensive understanding of how employees can effectively counterbalance the impact of AS through higher levels of strategic EI. Examining core affect as a mediator offers novel insights into coping mechanisms in response to AS experiences and their consequences.

The study acknowledges several limitations, as the scenarios may only partially capture the complexities of real-life AS situations. The focus on a specific context and the sample characteristics limit the generalizability of the findings. Future research should explore diverse organizational contexts and employ longitudinal designs.

The findings have practical implications for organizations as enhancing employees' EI skills through training programs interventions and integrating EI into organizational culture and leadership conduct.

The overall aim of this chapter is to focus on the process of, and issues warranting consideration for, the evaluation of educational interventions. In particular, to outline some key considerations for educators to follow when assessing the evidence-base for interventions they might be considering for use in their practice. Also, important considerations for those wishing to evaluate the effectiveness of an intervention they have initiated, as well as a useful checklist which summarises this all. Recognising that some readers of this chapter might be practitioners rather than researchers, it has been written with the practitioner in mind in, hopefully, a simple and practical way. There are, however, further opportunities for additional reading and resources signposted throughout for those who wish to read up on any of these areas more. In addition to those cited throughout and referenced in the Reference List at the end. There is also a section that provides the author’s Additional Recommended Readings and Resources to follow-up on. Readers might also want to refer to Chapter 3 in this book which discusses Single versus Multiple PPI approaches.

Introduction: Cost competitiveness, customer focus, and sustainability compliance are essential for new-age firms to survive and succeed in the VUCA market environment. This study examines how automobile corporations have improved cost competitiveness, productivity, and product quality.

Purpose: This study examines the importance of cost competitiveness, customer focus, and sustainability compliance for the long-term survival of organisations in VUCA markets, looking at the practical efforts made by automobile corporations to enhance cost competitiveness, productivity, and quality.

Methodology: The study utilises a comprehensive analysis of the strategies and initiatives implemented by the selected automobile companies. It involves a review of relevant literature, case studies, financial data analysis, and interviews with key industry experts, providing a holistic understanding of the actions taken by these organisations to achieve their goals.

Findings: The study reveals that cost competitiveness, customer focus, and sustainability compliance are critical factors for the long-term survival and success of organisations in the automotive industry. The analysed automobile companies have undertaken practical efforts to improve cost competitiveness, enhance productivity, and ensure high-quality products, enabling them to navigate the challenges and maintain a competitive edge.

Significance: The findings of this study contribute to a deeper understanding of the importance of cost competitiveness, customer focus, and sustainability compliance in the automotive industry. It highlights the need for organisations to constantly monitor both qualitative and quantitative profit to avoid complacency and ensure long-term efficiency. The study’s insights are relevant to businesses operating in other sectors, as they face similar challenges in the VUCA market environment.

This study investigates Rokkan's research programme in the light of the differences between case- and variables-based methodologies. Three phases of the research process are distinguished. Studying the way Rokkan actually proceeded in the research within his Europe project, we find that he follows the protocols of case-methodologies such as grounded theory. In the second phase of the research process, however, he constructs variables-based models as tools for his macro-historical comparisons. To get to variables from the sensitizing concepts coded in the first phase, Rokkan defines his variables as close to cases as possible: variables as nominal level typologies, types as variable values. He thus faces two interrelated dilemmas. First, a philosophy of science dissonance: he legitimates his research only with reference to a variable-methodology, while his research is thoroughly case based. Second, a paradox of double coding: using variable-based models in the second phase, the status of the knowledge available in the first phase memos is degraded. Rokkan cannot decide between the two main solutions to these dilemmas: The first solution is to discard his heterogeneous data, instead working only with homogeneous data that opens up to more consistently variables-oriented research. The second solution is to replace the notion of variables/variable values with typology/types, thereby returning to cases, pursuing comparative case reconstructions in the third phase of research. The study concludes in favour of the second solution.

Positive-framed and negative-framed messages were delivered to examine the effect of framing on intertemporal decisions through lab experiments while holding the level of financial literacy constant. The three big questions adopted by Lusardi and Mitchell were utilized to assess the financial literacy of our subjects before they were asked to complete 20 incentivized intertemporal decisions. A small, delayed reward and a slightly bigger one were incorporated into the intertemporal decisions with a delay of 30 days. The ordinary least square (OLS) shows that the negative relationship between financial literacy and discount rates was held when the delayed reward was small. Interestingly, when the delayed reward became slightly bigger, their discount rates were reduced significantly with the negatively framed message. These findings suggest that the negatively framed message can motivate individuals to save for a greater return in the real world. Lastly, subjects with the highest level of financial literacy were not responsive to the magnitude effect, proving that a financial literacy program is essential to strengthen the individual's financial plan and reduce their discount rates in the developing country context.

In the stock market, herding behavior occurs when investors mimic the actions of others in their investment decisions. As a result, the market becomes inefficient and speculative bubbles form. This study aims to investigate the relationship between information, overconfidence, market sentiment, experience and national culture, and herding behavior among Malaysian investors. A total of 400 questionnaires are distributed to bank institutions' investors. The survey design based on cross-sectional data is analyzed using the Partial Least Squares Structural Equation Model. The results indicate that information, market sentiment, experience, and national culture are positively related to herding behavior, while overconfidence has no effect. With this, the government should strengthen regulations to prevent the dissemination of misleading information. Moreover, investors are encouraged to overcome narrow thinking by expanding their understanding of different cultures when making investment decisions.

The development of information technologies has led to a considerable transformation in human resource management from conventional or commonly known as personnel management to modern one. Data mining technology, which has been widely used in several applications, including those that function on the web, includes clustering algorithms as a key component. Web intelligence is a recent academic field that calls for sophisticated analytics and machine learning techniques to facilitate information discovery, particularly on the web. Human resource data gathered from the web are typically enormous, highly complex, dynamic, and unstructured. Traditional clustering methods need to be upgraded because they are ineffective. Standard clustering algorithms are enhanced and expanded with optimization capabilities to address this difficulty by swarm intelligence, a subset of nature-inspired computing. We collect the initial raw human resource data and preprocess the data wherein data cleaning, data normalization, and data integration takes place. The proposed K-C-means-data driven cuckoo bat optimization algorithm (KCM-DCBOA) is used for clustering of the human resource data. The feature extraction is done using principal component analysis (PCA) and the classification of human resource data is done using support vector machine (SVM). Other approaches from the literature were contrasted with the suggested approach. According to the experimental findings, the suggested technique has extremely promising features in terms of the quality of clustering and execution time.

In times of crisis, such as the Covid-19 global pandemic, journalists who write about biomedical information must have the strategic aim to be clearly and easily understood by everyone. In this study, we assume that journalistic discourse could benefit from language redundancy to improve clarity and simplicity aimed at science popularization. The concept of language redundancy is theoretically discussed with the support of discourse analysis and information theory. The methodology adopted is a corpus-based qualitative approach. Two corpora samples with Brazilian Portuguese (BP) texts on Covid-19 were collected. One with texts from a monthly science digital magazine called Pesquisa FAPESP aimed at students and researchers for scientific information dissemination and the other with popular language texts from a news Portal G1 (Rede Globo) aimed at unspecified and/or non-specialized readers. The materials were filtered with two descriptors: “vaccine” and “test.” Preliminary analysis of examples from these materials revealed two categories of redundancy: paraphrastic and polysemic. Paraphrastic redundancy is based on concomitant language reformulation of words, sentences, text excerpts, or even larger units. Polysemic redundancy does not easily show material evidence, but is based on cognitively predictable semantic association in socio-cultural domains. Both kinds of redundancy contribute, each in their own way, to improving text readability for science popularization in Brazil.

To predict the future of the business and implement successful changes, a credit analyst must make quick decisions about the economics and assets of their clients. Because the marketplace is constantly changing, companies that lack the interpersonal skills necessary to communicate with their customers run the risk of falling behind the competition and becoming obsolete. The objective of this research was to assess whether credit analysts in Peruvian banks that used digital resources also improved their communication and interpersonal skills. The study was quantitative in nature, with an applied and correlational design that lacked an experimental component. The sample consisted of 109 credit analysts from four different Peruvian banks (Interbank, Scotiabank, BBVA, and BCP). Two questionnaires were used in this survey; both were submitted to expert review for validation before being submitted for use, and their reliability was determined using Cronbach's alpha. In terms of use of digital resources (59.5%) and mastery of interpersonal skills (61.3%), credit analysts were at the average. Conclusions the p-value for the correlation between credit analysts' use of digital resources and their soft skills in Peruvian banks was less than 0.05, indicating a direct and strong link between these two factors. The Rho correlation coefficient was 0.738.