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Social media fatigue (SMF) has been widely recognized; however, previous studies have included various concepts into a single fatigue construct. Fatigue has typically been explored from the stressor-strain-outcome (SSO) or stimulus-organism-response (SOR) perspectives. To further investigate SMF, the authors split it into the two constructs of exhaustion and disinterest. Furthermore, the authors introduced the concept of emotional labor and identified rules that may affect surface and deep acting strategies.

The authors designed and conducted a survey to collect data from social networking platform users.

Results from 364 users of social networking platforms supported most of the authors' hypotheses. First, most of the display rules affect the choice of deep or surface acting. Second, both types of acting lead to exhaustion, but only surface acting leads to disinterest. Third, discontinuance intention is affected by both types of fatigue.

This study contributes to SMF research by adding more antecedents (deep and surface acting) based on the emotional labor perspective and showing the impacts of communication rules on emotional labor. In addition, this study also distinguishes disinterest-style fatigue from exhaustion.

The authors construct two time-varying political connection (PC) indexes to measure a firm's political tendencies toward ruling and opposing parties and analyze whether a firm with ruling party tendencies obtains better bank loan contracts compared to the contracts obtained by a firm with opposing party tendencies and a firm with fixed PC tendencies.

Linguistic text mining is used to construct the two time-varying PC indexes from news sources that reflect the tone and frequencies of characteristic texts to determine a firm's tendencies to favor the ruling or opposing parties.

The results show that varying PC firms connected to the ruling party receive preferential loan contracts when their political tendencies increase but varying PC firms connected to the opposition party do not. In contrast, fixed PC firms gain similar benefits only when the connection is determined in the presidential election year but not in other years. Firms supporting two parties receive minimal financial rewards in terms of loan terms.

In past studies, once a firm is identified as having a connection with a political party, it is assumed to have PC throughout the sample period (i.e. fixed PC firms). The authors lift this assumption and examine how varying PC affect bank loan contracts. The two time-varying PC indexes can identify a firm's more immediate party tendencies and more precise effects of a firm's party tendencies on bank loan contracts.

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.

Clinically, it is often observed that autistic people may have a heightened need for rules and may find rule violations very distressing. It is clinically plausible that autistic individuals may be prone to hyper-morality and greater reactivity and adverse experiences arising from moral threats and violations. Such adverse experiences may, in some instances, lead to moral distress (MD) or in more extreme cases moral injury. Thus, this study aims to examine how MD can operate in the context of autism.

The authors explore clinical hypotheses on how MD can intersect with different features of autism by drawing on clinical and research knowledge of autism spectrum disorder and how it contextualises experiences of morality.

Based on a review of the literature and theory, the authors hypothesise that autistic individuals may be more prone to MD where they have a lower threshold for MD. As a result of this lower threshold, they may have more frequent exposure to MD, experience more immediate and intense subjective reactions to moral transgressions, for more protracted periods. Also, they may find it more difficult to over-ride and neutralise moral outrage. As a result, they may be more susceptible to mental health sequelae and impaired social and occupational functioning. Practical recommendations are made for clinicians supporting people with autism with a propensity for MD or moral injury, to improve their quality of life.

Practical recommendations are made for clinicians supporting people with autism with a propensity for MD or moral injury, to improve their quality of life.

Understanding MD in an autistic context is important for detecting and treating the adverse impacts of MD on autistic individuals. Importantly, erroneous preconceptions about moral reasoning in autism need to be mitigated to fully understand the moral experiences and harness the many strengths of people with autism.

This study applies Garfinkel’s (1967) concept of ‘breaching experiment’ to explore the impact of COVID-19-induced disruptions on the ‘emotion management’ practices of residential care workers in the United Kingdom and Germany. It examines the influence of professional feeling rules on workers, emphasizing the prescribed importance of displaying affective, empathetic concern for residents’ health and well-being. Findings demonstrate that authenticity and adherence to professional feeling rules in relation to emotional management are not mutually exclusive. The authors underscore how adherence to professional feeling rules upholds authentic care by reinforcing a professional ethos, which acts as a cornerstone motivating residential care workers. Ultimately, the study showcases how a professional ethos substantiates altruistic motivations, guiding proficient emotion management practices among care workers. It highlights how these workers drew upon their personal understanding and experiences to determine the appropriate emotions to express while providing care for residents amid the unprecedented challenges of the pandemic.

In this study, we attempt to investigate and examine the correlations among enterprise culture (EC), business ethic rules (BERs) and talented human resource supply chain management (THRSCM) in service SMEs in the Middle East region.

This study is quantitative in nature and adopts the quantitative-deductive hypothesis testing approach. To do this, a self-administrated survey was used and carried out to reach managers, human resource (HR) staff and workers from various small and medium-sized enterprises (SMEs) in the service sector that are listed in the Chambers of the Industries of Qatar, Saudi Arabia, the United Arab Emirates and Jordan in the Middle Eastern countries.

The empirical findings show that THRSCM and the BERs have a strong, positive correlation. Further, it found that there is also a strong and positive correlation between the EC and the BERs. As a result, THRSCM and EC can be extremely important in advancing and implementing BERs in SME service businesses. HR staff members should receive greater attention when implementing the BERs to accomplish the company’s goals and give customers a positive image of their enterprises. The HRM division and the company must be deeply aware of the significance of the BERs in their enterprises.

These findings can give managers, executives and HR staff helpful information to support the creation and upkeep of efficient business ethics rules inside their service SMEs.

Because there is not much study on the relationships between THRSCM, EC and BERs in the Middle East, this article attempts to investigate these relationships and consider them a benchmark for other future studies in ethics. Furthermore, it significantly influences service SMEs in the Middle East region.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2023-0763.

This study examines the importance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand. To this end, the authors construct a small open economy New Keynesian dynamic stochastic general equilibrium (DSGE) model. The model encompasses several essential characteristics, including incomplete financial markets, incomplete exchange rate pass-through, deviations from the law of one price and a banking sector. The authors consider generalized Taylor rules, in which policymakers adjust policy rates in response to output, inflation, credit growth and exchange rate fluctuations. The marginal likelihoods are then employed to investigate whether the central bank responds to fluctuations in the exchange rate and credit growth.

This study constructs a small open economy DSGE model and then estimates the model using Bayesian methods.

The authors demonstrate that the monetary authority does target exchange rates, whereas there is no evidence in favor of incorporating credit growth into the policy rules. These findings survive various robustness checks. Furthermore, the authors demonstrate that domestic shocks contribute significantly to domestic business cycles. Although the terms of trade shock plays a minor role in business cycles, it explains the most significant proportion of exchange rate fluctuations, followed by the country risk premium shock.

This study is the first attempt at exploring the relevance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand.

This study aims to investigate the influence of CEO attire formality on consumers’ perceptions of corporate image, drawing on first impression theory and spillover effect theory.

Four experimental studies were conducted to test the proposed effect, the underlying mechanism and the boundary condition.

The formality of CEO attire significantly influences consumers’ perceptions of corporate image. Specifically, formal CEO attire creates a stronger perception of corporate authority among consumers, mediated by perceived rule-following of the CEO. In contrast, informal CEO attire leads to a stronger perception of corporate friendliness, mediated by perceived psychological distance of the CEO. Moreover, a matching effect exists between the type of industry and CEO attire formality, where consumers perceive a greater match between authoritative industries and formally dressed CEOs, and between friendly industries and informally dressed CEOs. This alignment strengthens consumers’ corporate attitudes.

The findings offer valuable insights for CEOs aiming to foster a positive image through their attire, providing strategic guidance for aligning corporate image with industry characteristics.

This research extends the understanding of how consumers’ perceptions of CEO attire can spill over to affect the corporate image, offering a novel perspective on corporate image communication.

Project scheduling plays an essential role in the implementation of a project due to the limitation of resources in practical projects. However, the existing research tend to focus on finding suitable algorithms to solve various scheduling problems and fail to find the potential scheduling rules in these optimal or near-optimal solutions, that is, the possible intrinsic relationships between attributes related to the scheduling of activity sequences. Data mining (DM) is used to analyze and interpret data to obtain valuable information stored in large-scale data. The goal of this paper is to use DM to discover scheduling concepts and obtain a set of rules that approximate effective solutions to resource-constrained project scheduling problems. These rules do not require any search and simulation, which have extremely low time complexity and support real-time decision-making to improve planning/scheduling.

The resource-constrained project scheduling problem can be described as scheduling a group of interrelated activities to optimize the project completion time and other objectives while satisfying the activity priority relationship and resource constraints. This paper proposes a new approach to solve the resource-constrained project scheduling problem by combining DM technology and the genetic algorithm (GA). More specifically, the GA is used to generate various optimal project scheduling schemes, after that C4.5 decision tree (DT) is adopted to obtain valuable knowledge from these schemes for further predicting and solving new scheduling problems.

In this study, the authors use GA and DM technology to analyze and extract knowledge from a large number of scheduling schemes, and determine the scheduling rule set to minimize the completion time. In order to verify the application effect of the proposed DT classification model, the J30, J60 and J120 datasets in PSPLIB are used to test the validity of the scheduling rules. The results show that DT can readily duplicate the excellent performance of GA for scheduling problems of different scales. In addition, the DT prediction model developed in this study is applied to a high-rise residential project consisting of 117 activities. The results show that compared with the completion time obtained by GA, the DT model can realize rapid adjustment of project scheduling problem to deal with the dynamic environment interference. In a word, the data-based approach is feasible, practical and effective. It not only captures the knowledge contained in the known optimal scheduling schemes, but also helps to provide a flexible scheduling decision-making approach for project implementation.

This paper proposes a novel knowledge-based project scheduling approach. In previous studies, intelligent optimization algorithm is often used to solve the project scheduling problem. However, although these intelligent optimization algorithms can generate a set of effective solutions for problem instances, they are unable to explain the process of decision-making, nor can they identify the characteristics of good scheduling decisions generated by the optimization process. Moreover, their calculation is slow and complex, which is not suitable for planning and scheduling complex projects. In this study, the set of effective solutions of problem instances is taken as the training dataset of DM algorithm, and the extracted scheduling rules can provide the prediction and solution of new scheduling problems. The proposed method focuses on identifying the key parameters of a specific dynamic scheduling environment, which can not only reproduces the scheduling performance of the original algorithm well, but also has the ability to make decisions quickly under the dynamic interference construction scenario. It is helpful for project managers to implement quick decisions in response to construction emergencies, which is of great practical significance for improving the flexibility and efficiency of construction projects.

South Africa lags significantly in mathematics achievement on international benchmarking tests, which has led to several interventions aimed at improving mathematics attainment in the country. Drawing on the theoretical work of Vygotsky, Leontiev and Engeström, this chapter reports on one such initiative that implemented computer technology into disadvantaged schools in the apple growing district of the Western Cape. Contrary to expectations, the object of the lesson became control over students' actions, rather than a mathematical object aimed at developing students' understanding of the subject. The teacher adopted what I call a defensive position in relation to the novel technology, tightening pace and sequencing in these lessons. I draw on Ratnam's work into ‘excessive entitlement’ to illustrate that this teacher's defensive posture regarding technology emanates from a need to exert complete power over the content taught in a lesson and leads her to reject the novel technology in favour of traditional methods. While interviews with the teacher in this study indicated that she felt she promoted student dialogue and more symmetrical power relations in her classes through group work, this is not seen in the data. This is explained in relation to teachers' excessive entitlement to ‘owning’ the knowledge in their classrooms through maintaining control over the rules of the system. I pull on Cultural-Historical Activity Theory (CHAT) to illuminate how the activity of teaching in a classroom affords and constrains what the teacher is able to achieve, often making them feel excessively entitled to push back reform.