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Drawing on conservation of resources theory, this study aims to examine how employees’ experiences of excessive workloads may direct them away from efforts to share knowledge with other organizational members, as well as the circumstances in which this process is more or less likely. To untangle the process, the authors predict a mediating role of job dissatisfaction and moderating roles of two complementary resources that help employees cope with failure: resilience as a personal resource and organizational forgiveness as an organizational resource.

Survey data were gathered from employees of an organization that operates in the construction retail sector. The Process macro provides an empirical test of the moderated mediation dynamic that underpins the proposed conceptual framework.

The statistical findings affirm that an important channel through which employees’ perceptions that their work demands are unreasonable escalate into a diminished propensity to share knowledge is their lack of enthusiasm about their jobs. Their ability to recover from challenging work situations and their beliefs that the organization does not hold grudges against people who commit mistakes both mitigate this harmful effect.

For organizational practitioners, this research shows that when employees feel frustrated about extreme work pressures, the resource-draining situation may escalate into diminished knowledge sharing, which might inadvertently undermine their ability to receive valuable feedback for dealing with the challenges. From a positive perspective, individual resilience and organizational forgiveness represent resources that can protect employees against this negative spiral.

This study explicates an unexplored harmful effect of strenuous workloads on knowledge sharing, which is explained by employees’ beliefs that their organization fails to provide satisfactory job experiences. This effect also is mitigated to the extent that employees can draw from valuable personal and organizational resources.

This paper attempts to explain the phenomenon that Macau has a parliament (Legislative Assembly) and mass suffrage but no political parties.

This paper reviews the development process of “parliament – mass suffrage – political party” in Hong Kong and Macau and tries to explain why Macau does not have a party using comparative research methods.

The political party development of Hong Kong and Macau was influenced by both the (former) colonial power and China, and whether there were political parties in these two regions was the result of the game between China and the (former) colonial power. China hoped to limit the development of party politics in the two regions. Since Britain felt reluctant to cooperate with China, political parties in Hong Kong developed. At the same time, Portugal chose to defer to China, which led Macau not to have a political party.

Existing studies have yet to explain why there are no political parties in Macau, and this paper is the first attempt to do so.

The occupational health risk associated with the production of prefabricated concrete components is often overlooked. This paper will use a damage assessment and cyclic mitigation (DACM) model to provide individualized exposure risk assessment and corresponding mitigation management measures for workers who are being exposed.

The DACM model is proposed based on the concept of life cycle assessment (LCA). The model uses Monte-Carlo simulation for uncertainty risk assessment, followed by quantitative damage assessment using disability-adjusted life year (DALY). Lastly, sensitivity analysis is used to identify the parameters with the greatest impact on health risks.

The results show that the dust concentration is centered around the mean, and the fitting results are close to normal distribution, so the mean value can be used to carry out the calculation of risk. However, calculations using the DACM model revealed that there are still some work areas at risk. DALY damage is most severe in concrete production area. Meanwhile, the inhalation rate (IR), exposure duration (ED), exposure frequency (EF) and average exposure time (AT) showed greater impacts based on the sensitivity analysis.

Based on the comparison, the DACM model can determine that the potential occupational health risk of prefabricated concrete component (PC) factory and the risk is less than that of on-site construction. It synthesizes field research and simulation to form the entire assessment process into a case-base system with the depth of the cycle, which allows the model to be continuously adjusted to reduce the occupational health damage caused by production pollution exposure.

Supply chain resilience and knowledge management (KM) processes have received increasing attention from researchers and practitioners. Nevertheless, previous studies often treat the two streams of literature independently. Drawing on the knowledge-based theory, this study aims to reconcile these two different streams of literature and examine how and when KM processes influence supply chain resilience.

This research develops a conceptual model to test a sample of data from 203 Chinese manufacturing firms using a structural equation modeling method. Specifically, the current study empirically examines how KM processes affect different forms of supply chain resilience (supply chain readiness, responsiveness and recovery) and examines the moderating effect of blockchain technology adaptation and organizational inertia on the relationship between KM processes and supply chain resilience.

The findings show that KM processes positively affect three dimensions of supply chain resilience, i.e., supply chain readiness, responsiveness and recovery. Besides, the study reveals that blockchain technology adoption positively moderates the relationships between KM processes and supply chain resilience, whereas organizational inertia negatively moderates these above relationships.

This research linked the two research areas of supply chain resilience and KM processes, further bridging the gap in the research exploration of KM in the supply chain field. Next, this study contributes to supply chain resilience research by investigating how KM systems positively impact supply chain readiness, responsiveness and recovery. In addition, this study found a moderating effect of blockchain technology adaption and organizational inertia on the relationship between KM processes and supply chain resilience. These findings provide a reference for Chinese manufacturing firms to strengthen supply chain resilience, achieve secure supply chain operations and gain a competitive advantage in the supply chain. This studys’findings advance the understanding of supply chain resilience and provide practical implications for supply chain managers.

The purpose of this study is to investigate the antecedent factors influencing e-loyalty toward e-wallet payment apps in developing countries (e.g. Jordan). This study also investigates the mediating role of perceived usefulness (PU) and the moderating role of electronic word of mouth (e-WOM) toward these apps.

An online questionnaire was used for data collection from 251 actual users of e-wallet payment apps. To estimate and test the research-proposed model, the partial least squares structural equation modeling (PLS-SEM) was employed.

The results mainly confirm that perceived trust (PT), perceived financial cost (PFC) and perceived ease of use were found to be determinants of PU; perceived security (PS), PT, PFC, perceived ease of use and perceived enjoyment (PE) were found to be determinants of e-satisfaction, whereas e-satisfaction and e-WOM were found to be determinants of e-loyalty toward e-wallet payment apps. Likewise, the results support the significant effect of the moderating effect of e-WOM. Conversely, the direct and indirect impact of PU and perceived health benefits (PHB) on e-satisfaction is not supported; therefore, hypotheses H4, H5 and H9 were rejected.

This study contributes to the understanding of the critical success factors underlying e-wallet apps during and post-COVID-19 era, which can help policymakers in banks and other financial institutions (service providers) to increase the diffusion rate of financial inclusion by the usage of e-wallet apps.

The COVID-19 outbreak reached a critical stage when it became imperative for public health systems to act decisively and design potential behavioral operational strategies aimed at containing the pandemic. Isolation through social distancing played a key role in achieving this objective. This research study examines the factors affecting the intention of individuals toward social distancing in India.

A correlation study was conducted on residents from across Indian states (N = 499). Online questionnaires were floated, consisting of health belief model and theory of planned behavior model, with respect to social distancing behavior initially. Finally, structural equation modeling was used to test the hypotheses.

The results show that perceived susceptibility (PS), facilitating conditions (FC) and subjective norms are the major predictors of attitude toward social distancing, with the effect size of 0.277, 0.132 and 0.551, respectively. The result also confirms that the attitude toward social distancing, perceived usefulness of social distancing and subjective norms significantly predict the Intention of individuals to use social distancing with the effect size of 0.355, 0.197 and 0.385, respectively. The nonsignificant association of PS with social distancing intention (IN) (H1b) is rendering the fact that attitude (AT) mediates the relationship between PS and IN; similarly, the nonsignificant association of FC with IN (H5) renders the fact that AT mediates the relationship between FC and IN.

The results of the study are helpful to policymakers to handle operations management of nudges like social distancing.

The research is one of its kind that explores the behavioral aspects of handling social nudges through FC.

The Internet of Things (IoT) offers substantial potential for improving efficiency and effectiveness in various applications, notably within the domain of smart construction. Despite its growing adoption within the Architecture, Engineering, and Construction (AEC) industry, its utilization remains limited. Despite efforts made by policymakers, the shift from traditional construction practices to smart construction poses significant challenges. Consequently, this study aims to explore, compare, and prioritize the determinants that impact the acceptance of the IoT among construction practitioners.

Based on the integrated model of Unified Theory of Acceptance and Use of Technology (UTAUT2), Task-Technology Fit (TTF), and perceived risk. A cross-sectional survey was administered to 309 construction practitioners in China, and the collected data were analyzed using structural equation modeling (SEM) to test the proposed hypotheses.

The findings indicate that TTF, performance expectancy, effort expectancy, hedonic motivation, facilitating conditions, and perceived risk exert significant influence on construction practitioners’ intention to adopt IoT. Conversely, social influence and habit exhibit no significant impact. Notably, the results unveil the moderating influence of gender on key relationships – specifically, performance expectancy, hedonic motivation, and habit – in relation to the behavioral intention to adopt IoT among construction practitioners. In general, the model explains 71% of the variance in the behavioral intention to adopt IoT, indicating that the independent constructs influenced 71% of practitioners’ intentions to use IoT.

These findings provide both theoretical support and empirical evidence, offering valuable insights for stakeholders aiming to gain a deeper understanding of the critical factors influencing practitioners’ intention to adopt IoT. This knowledge equips them to formulate programs and strategies for promoting effective IoT implementation within the AEC field.

This study contributes to the existing literature by affirming antecedents and uncovering moderators in IoT adoption. It enhances the existing theoretical frameworks by integrating UTAUT2, TTF, and perceived risk, thereby making a substantial contribution to the advancement of technology adoption research in the AEC sector.

The unprecedented pandemic of COVID-19 is not a typical crisis. This crisis has irrevocably altered human behavior, most notably consumption behavior. The uncertainty caused due to economic insecurity and fears of death have resulted in a paradigm shift away from consumer materialism and toward consumer spiritualism. The present study examines the effect of various dimensions of “spirituality” on consumers’ conspicuous consumption of fashion. The study employs a descriptive empirical research design to determine the impact of multiple dimensions of spirituality on the conspicuous consumption of Generation Z in India. These dimensions include General spirituality belief, Global personal spirituality and reincarnation spirituality. Additionally, the moderating effect of dispositional positive emotion on the relationships mentioned above has been investigated.

The data were accumulated through purposive sampling from 517 Generation Z consumers and analyzed using structural equation modeling.

Reincarnation, general personal and global personal spirituality had a direct positive impact on conspicuous consumption of fashion. Dispositional positive emotion had a positive moderation effect between the reincarnation, general personal and global personal spirituality and conspicuous consumption.

The study will assist fashion brands and retailers in better understanding consumer behavior and associated opportunities and threats post COVID-19. For merchants and business owners in emerging countries, this study will help them to apply new techniques for keeping customers. It is useful to evaluate a shopper’s views towards spirituality, disposition and conspicuous consumption.

This article presents two Brazilian Portuguese corpora collected from different media concerning public security issues in a specific location. The primary motivation is supporting analyses, so security authorities can make appropriate decisions about their actions.

The corpora were obtained through web scraping from a newspaper's website and tweets from a Brazilian metropolitan region. Natural language processing was applied considering: text cleaning, lemmatization, summarization, part-of-speech and dependencies parsing, named entities recognition, and topic modeling.

Several results were obtained based on the methodology used, highlighting some: an example of a summarization using an automated process; dependency parsing; the most common topics in each corpus; the forty named entities and the most common slogans were extracted, highlighting those linked to public security.

Some critical tasks were identified for the research perspective, related to the applied methodology: the treatment of noise from obtaining news on their source websites, passing through textual elements quite present in social network posts such as abbreviations, emojis/emoticons, and even writing errors; the treatment of subjectivity, to eliminate noise from irony and sarcasm; the search for authentic news of issues within the target domain. All these tasks aim to improve the process to enable interested authorities to perform accurate analyses.

The corpora dedicated to the public security domain enable several analyses, such as mining public opinion on security actions in a given location; understanding criminals' behaviors reported in the news or even on social networks and drawing their attitudes timeline; detecting movements that may cause damage to public property and people welfare through texts from social networks; extracting the history and repercussions of police actions, crossing news with records on social networks; among many other possibilities.

The work on behalf of the corpora reported in this text represents one of the first initiatives to create textual bases in Portuguese, dedicated to Brazil's specific public security domain.

This study aims to quantitatively consolidate the research conducted over the past four decades on how internal branding activities drive employee commitment. It summarizes several operationalizations of internal branding and tests the moderating effect of employee’s personal characteristics and job characteristics on the relationship between internal branding and employee commitment.

This paper uses meta-analysis as the research methodology. The analysis includes a sample of 65 studies (from 62 published works), yielding 226 effect sizes (coded into 82 composite effect sizes) over an aggregated sample of 21,706 respondents.

This study finds that brand communication, brand-centered human resource management (HRM), training and development, organizational support and culture, brand-centered leadership and an excellent reward system are the key operationalizations of internal branding. Furthermore, employee’s personal (education, age and gender) and job (tenure, work status and level of customer orientation) characteristics significantly moderate the internal branding–employee commitment relationship.

Limited empirical literature on some of the internal branding operationalizations such as brand-centered HRM and rewards has curbed the scope of moderator analysis.

This paper proposes some effective ways of implementing internal branding strategies and provides support for boundary conditions that brand managers should consider to strengthen the impact of internal branding activities on employee commitment.

As per the authors’ knowledge, this paper is among the few quantitative consolidations of four decades of research on the internal branding–employee commitment relationship.