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The lack of a definite standard for determining the sample size in qualitative research leaves the research process to the initiative of the researcher, and this situation overshadows the scientificity of the research. The primary purpose of this research is to propose a model by questioning the problem of determining the sample size, which is one of the essential issues in qualitative research. The fuzzy logic model is proposed to determine the sample size in qualitative research.

Considering the structure of the problem in the present study, the proposed fuzzy logic model will benefit and contribute to the literature and practical applications. In this context, ten variables, namely scope of research, data quality, participant genuineness, duration of the interview, number of interviews, homogeneity, information strength, drilling ability, triangulation and research design, are used as inputs. A total of 20 different scenarios were created to demonstrate the applicability of the model proposed in the research and how the model works.

The authors reflected the results of each scenario in the table and showed the values for the sample size in qualitative studies in Table 4. The research results show that the proposed model's results are of a quality that will support the literature. The research findings show that it is possible to develop a model using the laws of fuzzy logic to determine the sample size in qualitative research.

The model developed in this research can contribute to the literature, and in any case, it can be argued that determining the sample volume is a much more effective and functional model than leaving it to the initiative of the researcher.

The article aims to establish whether the degree of aversion to inflation and the responsiveness to deviations from potential output have changed over time.

This paper assesses time variation in monetary policy rules by applying a time-varying parameter generalised methods of moments (TVP-GMM) framework.

Using monthly data until December 2022 for five inflation targeting countries (the UK, Canada, Australia, New Zealand, Sweden) and five countries with alternative monetary regimes (the US, Japan, Denmark, the Euro Area, Switzerland), we find that monetary policy has become more averse to inflation and more responsive to the output gap in both sets of countries over time. In particular, there has been a clear shift in inflation targeting countries towards a more hawkish stance on inflation since the adoption of this regime and a greater response to both inflation and the output gap in most countries after the global financial crisis, which indicates a stronger reliance on monetary rules to stabilise the economy in recent years. It also appears that inflation targeting countries pay greater attention to the exchange rate pass-through channel when setting interest rates. Finally, monetary surprises do not seem to be an important determinant of the evolution over time of the Taylor rule parameters, which suggests a high degree of monetary policy transparency in the countries under examination.

It provides new evidence on changes over time in monetary policy rules.

Amidst unpredictable and turbulent periods, such as the COVID-19 pandemic, service organization’s responses are required to be innovative, adaptable and resilient. The purpose of this study is to explore the utilization of both reconfiguration and transformational strategies as instruments for cultivating resilience and advancing sustainability in service organizations.

The study examines a proposed resilience model using fuzzy logic. The research also used a semantic differential scale to capture nuanced and intricate attitudes. Finally, to augment the validity of the resilience model, a measurement scale was formulated using business mathematics and expert opinions.

Although investing in resilience training can help organizations gain control and maintain their operations in times of crisis, it may not directly help service organizations understand the external turmoil, seek available resources or create adaptive remedies. Conversely, high levels of reconfiguration and transformation management vigour empower a service organization’s revolutionary, malleable vision, organizational structure and decision-making processes, welcoming talented and innovative employees to enhance capabilities during crises.

The resilience model bestows a comprehensive understanding of the pertinence of building resilience for service organizations identifying the antecedents that influence the adoption of these strategies and introduces a range of theoretical perspectives that empowers service organizations to conceptualize and plan for building resilience. The research guides service organizations to become more resilient to external shocks and adapt to changing circumstances by diversifying their offerings, optimizing their resources and adopting flexible work arrangements. The study elaborates on the enhancement of resilience, increasing innovation, improving efficiency and enhancing customer satisfaction for service organizations to remain competitive and contribute to positive social and economic outcomes through the adoption of both reconfiguration and transformational strategies.

The study also guides the service organizations to become more resilient to external shocks and adapt to changing circumstances by diversifying their offerings, optimizing their resources and adopting flexible work arrangements. Rapid innovation and business model innovation are essential components, enabling service organizations to foster a culture of innovation and remain competitive. In addition, the adoption can lead to improved financial performance, job creation and economic growth, contributing to positive social and economic impacts.

The resilience model bestows a comprehensive understanding of the pertinence of building resilience for service organizations. It identifies the antecedents that influence the adoption of these strategies and introduces a range of theoretical perspectives that empowers service organizations to conceptualize and plan for building resilience. The research also provides a foundation for further investigation into the effectiveness of these strategies and their impact on organizational performance and sustainability. By better preparing service organizations for disruptions and uncertainties, this research triggers ameliorated organizational performance and sustainability.

Within the realm of the service industry, the present investigation has undertaken the development, quantification and scrutiny of both resilience and tenacity. In addition, it has delved into the intricate dynamics surrounding the influencing factors and antecedents that bear upon resilience, elucidating their consequential impact on the operational performance and outlook of service-oriented organizations. The findings derived from this research furnish valuable insights germane to enhancing operational efficacy and surmounting impediments within the sector.

The aim of this paper is to systematically review the literature published in recognized journals focused on recognition-based heuristics and their effect on investment management activities and to ascertain some substantial gaps related to them.

For doing research synthesis, systematic literature review approach was applied considering research studies published within the time period, i.e. 1980–2020. This study attempted to accomplish a critical review of 59 studies out of 118 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioural finance domain-related explicitly to recognition-based heuristics and their effect on investment management activities.

The survey and analysis suggest investors consistently rely on the recognition-based heuristic-driven biases when trading stocks, resulting in irrational decisions, and an investment strategy constructed by implementing the recognition-based heuristics, would not result in better returns to investors on a consistent basis. Institutional investors are less likely to be affected by these name-based behavioural biases in comparison to individual investors. However, under the context of ecological rationality, recognition-based heuristics work better and sometimes dominate the classical methods. The research scholars from the behavioural finance community have highlighted that recognition-based heuristics and their impact on investment management activities are high profile areas, needed to be explored further in the field of behavioural finance. The study of recognition-based heuristic-driven biases has been found to be insufficient in the context of emerging economies like Pakistan.

The skilful understanding and knowledge of the recognition-based heuristic-driven biases will help the investors, financial institutions and policy-makers to overcome the adverse effect of these behavioural biases in the stock market. This article provides a detailed explanation of recognition-based heuristic-driven biases and their influence on investment management activities which could be very useful for finance practitioners’ such as investor who plays at the stock exchange, a portfolio manager, a financial strategist/advisor in an investment firm, a financial planner, an investment banker, a trader/ broker at the stock exchange or a financial analyst. But most importantly, the term also includes all those persons who manage corporate entities and are responsible for making its financial management strategies.

Currently, no recent study exists, which reviews and evaluates the empirical research on recognition-based heuristic-driven biases displayed by investors. The current study is original in discussing the role of recognition-based heuristic-driven biases in investment management activities by means of research synthesis. This paper is useful to researchers, academicians, and those working in the area of behavioural finance in understanding the role that recognition-based heuristics plays in investment management activities.

Supervisor incivility and organizational gossip are two examples of dark organizational behaviors. Norm of reciprocity theory suggests that employees may develop revenge intentions after exposure to such behaviors while attributing blame to others. This study aims to empirically investigate the mediating effect of blaming others on the impact of supervisor incivility and negative organizational gossip on revenge intention.

Confirmatory factor analysis (CFA) was performed to test the measurement model. Structural equation model was used to test the research hypotheses based on data gathered in Turkey from restaurant employees in Mersin Marina selected by convenience sampling. Data set that consists of 239 questionnaires was subjected to CFA.

The findings show that negative organizational gossip and supervisor incivility increase to employees’ revenge intentions, and blaming others mediates the impact of supervisor incivility and negative organizational gossip no employees’ revenge intentions. In addition, blaming others mediates the impact of supervisor incivility and negative organizational gossip on employees’ revenge intentions.

Empirical study has not been encountered related to dark behaviors of (especially gossip, incivility, blame and revenge intention) restaurant managers and employees as a holistic model. Therefore, this paper contributes to organizational behavior literature. Moreover, this paper suggests to restaurant managers for supply to organizational peace.

This paper aims to investigate the association between negative tone in annual report narratives and future performance in the UK context. Under the principle-based approach in the UK, managers tend to bias the tone of narrative reports upward, as the reporting regime is more flexible than the rule-based approach in the USA. Consequently, any negative disclosure not mandated by regulators conveys credible information about a firm’s prospects.

This paper uses a sample of UK FTSE all-share non-financial companies from 2010 to 2019. The authors use the textual-analysis approach based on Loughran and McDonald (2011)’s wordlist (LM) to measure the negative tone in UK annual reports.

The results show a significant negative association between negative tone and future performance. Moreover, our further analyses suggest that only the negativity in the executive section of the annual disclosures correlates significantly with future performance. In summary, this study suggests that negativity does matter under the principle-based approach and can be used as an indicator of future performance.

In contrast to the literature arguing that only positivity has the power to affect a firm’s outcomes under the principle-based approach, the authors provide new empirical evidence suggesting that negativity also matters within the UK context and can be used as an indicator for future performance. Also, to the best of the authors’ knowledge, this is the first study to identify which section of the annual report is more informative about a firm’s future performance.

Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and cooperative obstacle avoidance.

This study draws inspiration from the recurrent state-space model and recurrent models (RPM) to propose a simpler yet highly effective model called the unmanned aerial vehicles prediction model (UAVPM). The main objective is to assist in training the UAV representation model with a recurrent neural network, using the soft actor-critic algorithm.

This study proposes a generalized actor-critic framework consisting of three modules: representation, policy and value. This architecture serves as the foundation for training UAVPM. This study proposes the UAVPM, which is designed to aid in training the recurrent representation using the transition model, reward recovery model and observation recovery model. Unlike traditional approaches reliant solely on reward signals, RPM incorporates temporal information. In addition, it allows the inclusion of extra knowledge or information from virtual training environments. This study designs UAV target search and UAV cooperative obstacle avoidance tasks. The algorithm outperforms baselines in these two environments.

It is important to note that UAVPM does not play a role in the inference phase. This means that the representation model and policy remain independent of UAVPM. Consequently, this study can introduce additional “cheating” information from virtual training environments to guide the UAV representation without concerns about its real-world existence. By leveraging historical information more effectively, this study enhances UAVs’ decision-making abilities, thus improving the performance of both tasks at hand.

The purpose of this paper is to explore the reintegration process of Wounded, Injured or Sick Employees (WISE) of the Dutch Military Armed Forces.

The research method is an exploratory, qualitative case study. A purposive sampling was drawn, including 10 WISE, and 6 reintegration stakeholders. A total of 16 interviews were conducted to explore the individual, organisational and socio-environmental factors that influence reintegration of WISE.

Findings show the importance of involvement and participation of members of the social environment in the reintegration process. Findings show that the complexity of the plethora of WISEs' injuries and disabilities requires a more person-centric reintegration approach with personalized-customized provisions, rather than a policy-driven approach to the reintegration, in order to enhance the reintegration experience and to arrive at beneficial individual and organisational reintegration outcomes.

This cross-sectional study on a limited sample of WISE and reintegration stakeholders does not allow for making inferences about the long-term effects of the reintegration process on reintegration outcomes of the wider population of WISE. Future longitudinal research, encompassing a larger sample, could examine the long-term career, organisational and societal implications of reintegration of WISE within and outside the Military Armed Forces.

This paper presents a “Wounded Warrior Workplace Reintegration Program”, aimed at deriving beneficial outcomes for all stakeholders involved in the reintegration trajectory.

This paper contributes to the literature by presenting a Model of Occupational Reintegration of WISE that considers the factors at an individual, social-environmental, and institutional level as determinants of successful reintegration.

The purpose of this study is to identify the main perspectives and trends in educational data mining (EDM) in the e-learning environment from a managerial perspective.

This paper proposes a systematic literature review to identify the main perspectives and trends in EDM in the e-learning environment from a managerial perspective. The study domain of this review is restricted by the educational concepts of e-learning and management. The search for bibliographic material considered articles published in journals and papers published in conferences from 1994 to 2023, totaling 30 years of research in EDM.

From this review, it was observed that managers have been concerned about the effectiveness of the platform used by students as it contains the entire learning process and all the interactions performed, which enable the generation of information. From the data collected on these platforms, there are improvements and inferences that can be made about the actions of educators and human tutors (or automatic tutoring systems), curricular optimization or changes related to course content, proposal of evaluation criteria and also increase the understanding of different learning styles.

This review was conducted from the perspective of the manager, who is responsible for the direction of an institution of higher education, to assist the administration in creating strategies for the use of data mining to improve the learning process. To the best of the authors’ knowledge, this review is original because other contributions do not focus on the manager.

Responding to calls for deeper analysis of the conceptual foundations of service infusion in manufacturing, this paper examines the underlying assumptions that: (i) manufacturing firms incorporating services follow a pathway, moving from pure-product to pure-service offerings, and (ii) profits increase linearly with this process. We propose that these assumptions are inconsistent with the premises of behavioural and learning theories.

Machine learning algorithms are applied to test whether a successive process, from a basic to a more advanced offering, creates optimal performance. The data were gathered through two surveys administered to USA manufacturing firms in 2021 and 2023. The first included a training sample comprising 225 firms, whilst the second encompassed a testing sample of 105 firms.

Analysis shows that following the base-intermediate-advanced services pathway is not the best predictor of optimal performance. Developing advanced services and then later adding less complex offerings supports better performance.

Manufacturing firms follow heterogeneous pathways in their service development journey. Non-servitised firms need to carefully consider their contextual conditions when selecting their initial service offering. Starting with a single service offering appears to be a superior strategy over providing multiple services.

The machine learning approach is novel to the field and captures the key conditions for manufacturers to successfully servitise. Insight is derived from the adoption and implementation year datasets for 17 types of services described in previous qualitative studies. The methods proposed can be extended to assess other process-based models in related management fields (e.g., sand cone).