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Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.

Stakeholder theory understands business in terms of relationships among stakeholders whose interests are mainly joint but may be occasionally conflicting. In the latter case, managers may need to make trade-offs between these interests. The purpose of this paper is to explore the nature of managerial decision-making about these trade-offs.

This paper draws on the ordonomic approach which sees business life to be rife with social dilemmas and locates the role of stakeholders in harnessing or resolving these dilemmas through engagement in rule-finding and rule-setting processes.

The ordonomic approach suggests that stakeholder interests trade-offs ought to be neither ignored nor avoided, but rather embraced and welcomed as an opportunity for bringing to fruition the joint interest of stakeholders in playing a better game of business. Stakeholders are shown to bear responsibility for overcoming the perceived trade-offs through the institutional management of social dilemmas.

For many stakeholder theorists, the nature of managerial decision-making about trade-offs between conflicting stakeholder interests and the nature of trade-offs themselves have been a long-standing point of contention. The paper shows that trade-offs may be useful for the value creation process and explicitly discusses managerial strategies for dealing with them.

Consumer-perceived review attitude determines consumer overall information adoption and is a core part of consumer’s online-shopping. This study aims to focus on factors that could influence consumer review attitude and can be used by marketers to shape individual information perception.

The study used the questionnaire method to collect data from online shoppers and the modelling of structural equations as an empirical approach to analyse the data.

The findings demonstrate that both systematic and heuristic cues impact the reviewer’s credibility and perceived website attitude differently, which, in turn, influence review attitude. Review characteristics, such as factuality, consistency and relevancy, have a positive relationship with reviewer credibility, while only review consistency and relevancy appears to have a relationship with review attitude. Website characteristics such as reputation, familiarity and social interactivity positively influence the website attitude, which positively influences review attitude. Apart from this, review skepticism has a significant negative relationship with review attitude.

This study could help to foster a positive attitude towards online reviews. Digital marketers need to motivate trusted reviewers to post consistent, fact-based reviews. Further improving the overall website reputation and interactivity could bring a positive attitude towards the reviews. Also, digital marketers must filter and avoid contradictory reviews or reviews that have a bipolar message and reviews expressing numerous emotions to enhance review relevance and consistency.

The current study addresses the need to understand the formation of consumer review attitude through both review and website characteristics using heuristic – systematic model. The paper captures the complex process undergone by the consumer to decipher review attitude and thereby extend the understanding of consumer information processing.

Due to the influence of complex and intersecting factors, self-governed public open spaces (POSs) (managed by local communities) are subject to collective action dilemmas such as tragedy of the commons (overexploitation), free-riding, underinvestment and mismanagement. This review paper adopts a multi-dimensional and multi-tier social-ecological system (SES) framework proposed by McGinnis and Ostrom, drawing on collective action theory to explore the key institutional-social-ecological factors that impact POS self-governance.

In this paper, Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) was utilized to systematically screen and review the relevant literature for the period from 2000 to 2023 in three databases: Web of Science, Scopus and Google Scholar. A total of 57 papers were chosen for in-depth analysis.

The literature review identified and categorized several variables associated with the self-organizing system of POS; consequently, an SES-based POS management framework was developed for the first time, consisting of 114 institutional-social-ecological sub-variables from different dimensions and three levels. Compared to ecological factors, among others, governance organizations, property-rights systems, socioeconomic attributes and actors' knowledge of SES have been commonly and primarily studied.

There is still room for the refinement of the conceptual SES-based POS collective action framework over the time (by adding in new factors), and indefinitely empirical research validating those identified factors is also worth to be undertaken, particularly testing how SES factors and interaction variables affect the POS quality (collective action).

The findings of this study can provide local policy insights and POS management strategies based on the identification of specific SES factors for relevant managers. Moreover, this research makes significant theoretical contributions to the integration of the SES framework and collective action theory with POS governance studies.

The aim of this paper is to explore the stakeholder exclusion practices of responsible leaders.

An interpretive multiple case analyses of seven responsibly led organisations was employed. Twenty-two qualitative interviews were undertaken to investigate and understand perceptions and practice of responsible leaders and their approach to stakeholder inclusion and exclusion.

The findings revealed new and surprising insights where responsible leaders compromised their espoused values of inclusivity through the application of a personal bias, resulting in the exclusion of certain stakeholders. This exclusivity practice focused on the informal evaluation of potential stakeholders’ values, and where they did not align with those of the responsible leader, these stakeholders were excluded from participation with the organisation. This resulted in the creation and continuity of a culture of shared moral purpose across the organisation.

This study focussed on responsible leader-led organisations, so the next stage of the research will include mainstream organisations (i.e. without explicit responsible leadership) to examine how personal values bias affects stakeholder selection in a wider setting.

The findings suggest that reflexive practice and critically appraising management methods in normative leadership approaches may lead to improvements in diversity management.

This paper presents original empirical data challenging current perceptions of responsible leader inclusivity practices and indicates areas of leadership development that may need to be addressed.

For ranking aggregation in crowdsourcing task, the key issue is how to select the optimal working group with a given number of workers to optimize the performance of their aggregation. Performance prediction for ranking aggregation can solve this issue effectively. However, the performance prediction effect for ranking aggregation varies greatly due to the different influencing factors selected. Although questions on why and how data fusion methods perform well have been thoroughly discussed in the past, there is a lack of insight about how to select influencing factors to predict the performance and how much can be improved of.

In this paper, performance prediction of multivariable linear regression based on the optimal influencing factors for ranking aggregation in crowdsourcing task is studied. An influencing factor optimization selection method based on stepwise regression (IFOS-SR) is proposed to screen the optimal influencing factors. A working group selection model based on the optimal influencing factors is built to select the optimal working group with a given number of workers.

The proposed approach can identify the optimal influencing factors of ranking aggregation, predict the aggregation performance more accurately than the state-of-the-art methods and select the optimal working group with a given number of workers.

To find out under which condition data fusion method may lead to performance improvement for ranking aggregation in crowdsourcing task, the optimal influencing factors are identified by the IFOS-SR method. This paper presents an analysis of the behavior of the linear combination method and the CombSUM method based on the optimal influencing factors, and optimizes the task assignment with a given number of workers by the optimal working group selection method.

Online reviews serve as valuable sources of information, reflecting tourists’ attentions, preferences and sentiments. However, although the existing research has demonstrated that incorporating online review data can enhance the performance of tourism demand forecasting models, the reliability of online review data and consumers’ decision-making process have not been given adequate attention. To address the aforementioned problem, the purpose of this study is to forecast tourism demand using online review data derived from the analysis of review helpfulness.

The authors propose a novel “identification-first, forecasting-second” framework. This framework prioritizes the identification of helpful reviews through a comprehensive analysis of review helpfulness, followed by the integration of helpful online review data into the forecasting system. Using the SARIMAX model with helpful online review data sourced from TripAdvisor, this study forecasts tourist arrivals in Hong Kong during the period from August 2012 to June 2019. The SNAÏVE/SARIMA model was used as the benchmark model. Additionally, artificial intelligence models including long short-term memory, back propagation neural network, extreme learning machine and random forest models were used to assess the robustness of the results.

The results demonstrate that online review data are subject to noise and bias, which can adversely affect the accuracy of predictions when used directly. However, by identifying helpful online reviews beforehand and incorporating them into the forecasting process, a notable enhancement in predictive performance can be realized.

First, to the best of the authors’ knowledge, this study is one of the first to focus on the data issue of online reviews on tourism arrivals forecasting. Second, this study pioneers the integration of the consumer decision-making process into the domain of tourism demand forecasting, marking one of the earliest endeavors in this area. Third, this study makes a novel attempt to identify helpful online reviews based on reviews helpfulness analysis.

While existing research has explored the association between supervisor support and turnover intention among construction workers, there is a notable gap in the literature concerning the potential mediating role of work engagement in elucidating this relationship, warranting further investigation. The paper, hence, aims to examine the mediating role of work engagement in the relationship between supervisor support and turnover intention among construction workers.

Based on the quantitative research method, the hypothesis was tested. The data were collected from 144 construction professionals using a structured questionnaire. Observed variables were tested using confirmatory factor analysis, and the mediating role relationship was validated using hierarchical regression.

The outcome of this study shows a significant positive impact of work engagement and supervisor support on employee turnover intention. The study further showed that work engagement plays a mediating role in the connection between supervisory support and the intention to turnover and improve project and business performance. Turnover intention, on the other hand, negatively affects project and organizational performance.

By enhancing employee work engagement and perceptions of supervisor support, the findings of this study may aid construction organizations in making better judgments regarding the likelihood of employee turnover. The effectiveness of the project and the organization will likely be greatly impacted.

The results of this study provide supporting evidence and advance efforts at reducing employee turnover intention through work engagement and supervisor support in improving project and organizational performance.

This study aims to test negotiation outcomes when bilinguals negotiate in a foreign rather than their native language. Decision research on the foreign language effect indicates that bilingual individuals may be less susceptible to framing bias when using a foreign language because they make less emotional and biased choices. With increasing international business activity, there is a pressing need to examine the effect of language on bilingual negotiators.

The authors tested the hypotheses using a two (task frame: gain vs loss) × 2 (language: foreign vs native) factorial design recruiting 246 Korean–English bilinguals. A negotiation simulation with three issues was used, and participants exchanged offers with a preprogrammed computer they believed to be a real counterpart.

There was no significant interaction effect between framing and language on the offers made, but the framing effect was mitigated and nonsignificant for negotiators who used their foreign language. The interaction between framing and language conditions significantly affected negotiators’ positive emotions and satisfaction with the negotiation.

The uniqueness of this paper is related to its effort to investigate the effect of negotiation language on a negotiator’s decision-making. Considering globalization and the increasing prevalence of international negotiations, this paper has implications for researchers and practitioners.

This study analyses the concept of happiness management based on the empirical validation of the interactions between emotional wage, organisational justice and happiness at work. It complements a holistic view of the management models used in recent corporate governance. This perspective explores the dimension’s emotional wage mediating role and influences on organisational justice and happiness at work. The effect of organisational justice on happiness at work is also analysed.

A quantitative, cross-sectional, descriptive and correlational study is proposed. A sample of 502 workers in the education sector in Costa Rica was selected. A structural equation model (PLS-SEM) was developed to test the proposed theoretical model. The SPSS-AMOS 23 and SmartPLS 4 computer programs are used for this purpose.

The results show that emotional wage has a positive impact on happiness at work and that it mediates positively between organisational justice and happiness at work. Developing organisational policies to include these variables as necessary resources for corporate governance is recommended.

The first limitation of this study is due to the type of sampling, which was purposive. The kind of population and the time of execution of this study were determining factors when deciding on the mode of application of the instrument. However, an attempt to reduce the bias associated with this element could be made by expanding the sample to as many respondents as possible. The second limitation was that the data were collected within a specific time frame. Longitudinal studies address Thcould. The third limitation stems from the scarcity of literature on happiness management. In this regard, this type of research currently needs to be explored in emerging economies. It makes it difficult to determine whether the empirical results obtained in this paper can be generalised to other territories in the global village. Moreover, the last limitation is that the authors of this research have only explored the moderating role of emotional pay in the relationship between the dimensions of organisational justice and happiness at work. It would be interesting to consider other mediating variables to have a clearer picture of the organisational justice–happiness at work construct from the happiness management approach.

As already indicated throughout this research, emotional wage, organisational justice and happiness at work are constructs that positively drive employee satisfaction, motivation and well-being. Human talent management strategies undertaken by organisations should encourage the adaptation of actions that stimulate employees' quality of life, corporate social responsibility and ethical management practices to be more competitive in today’s markets. It requires implementing the dynamic management models that provide internal customers with a high sense of belonging, job satisfaction and commitment to their professional performance. In other words, this will require robust leadership styles and corporate cultures that stimulate employee creativity, loyalty and innovation. For this reason, management of organisations must implement human resources policies to attract and retain creative talent through happy leadership. It requires, among other things that the philosophy of happiness management becomes a critical strategic resource for companies to promote nonfinancial benefits for employees, including emotional wage (Ruiz-Rodríguez et al., 2023).

In the current business environment, there has been a transformation in leadership styles, motivation and the development of a sense of belonging in organisations' human capital. Based on this trend, the study of happiness management becomes a social strategy to improve the conditions, in which the organisations compete to attract highly demanded human capital. It is why this research contributes elements that have an impact on citizenship by proposing the management models based on happiness at work and quality of life.

This study adds to the happiness management literature by including emotional wage, organisational justice and happiness at work in human resources and strategic management. It also contributes to the academic debate on the need to formulate organisational cultures that empower workers in their professional performance based on happiness and positive emotions.