Search results

This study aims to examine the effect of supervisor developmental feedback on employee silence behaviour by developing a moderated mediation model. The model focuses on the mediating role of role breadth self-efficacy and high activated positive affect underpinning the relationship between supervisor developmental feedback and employee silence behaviour, and the moderating role of interdependent self-construal.

The two-wave survey was conducted among 265 employees. Structural equation modelling was conducted to test the mediation and moderation mediation hypotheses.

Results indicated that high activated positive affect mediated the negative relationship between supervisor developmental feedback and employee silence behaviour. The authors also found that interdependent self-construal moderated the relationship between supervisor developmental feedback and role breadth self-efficacy, as well as the indirect effect of supervisor developmental feedback on employee silence behaviour via role breadth self-efficacy.

This empirical study provides preliminary evidence of the mediating role of breadth self-efficacy and high activated positive affect in the negative relationship between supervisor developmental feedback and employee silence behaviour. The moderated mediation results further show that the mediation of role breadth self-efficacy between supervisor developmental feedback is contingent on individual interdependent self-construal, such that the mediation effect is significant among individuals with high interdependent self-construal, but the mediation effect of high activated positive effect is independent of individual interdependent self-construal. The findings further extend boundary conditions (interdependent self-construal) that may constrain the effect of supervisor developmental feedback on role breadth self-efficacy and high activated positive affect. The research makes considerable contributions to the cognitive-affective personality system theory by specifying the cognitive and affective mechanisms between supervisor developmental feedback and employee silence behaviour, as well as the boundary conditions.

The COVID-19 pandemic has showcased the lack of resilience found in the global value chains (GVCs) of multinational enterprises (MNEs). Existing evidence shows that MNEs have only recently and slowly started recovering and attempting to rebuild the resilience of their GVCs. This paper analyzes the challenges/inhibitors faced by MNEs in building their resilience through their GVCs.

A four-stage hybrid model was used to identify the interrelationship among the identified inhibitors and to distinguish the most critical ones by ranking them. In the first stage, we employed a modified total interpretive structural modeling (m-TISM) approach to determine the inter-relationship among the inhibitors. Additionally, we identified the inhibitors' driving power and dependency by performing a matrix multiplication applied to classification (MICMAC) analysis. In the second stage, we employed the Pythagorean fuzzy analytic hierarchy process (PF-AHP) method to determine the weight of the criteria. The next stage followed, in which we used the Pythagorean fuzzy combined compromise solution (PF-CoCoSo) method to rank the inhibitors. Finally, we performed a sensitivity analysis to determine the robustness of the framework we had built based on the criteria and inhibitors.

We find business sustainability to have the highest importance and managerial governance as the most critical inhibitor hindering the path to resilience. Based on these insights, we derive four research propositions aimed at strengthening the resilience of such GVCs, followed by their implications for theory and practice.

Our findings contribute to the extant literature by uncovering key inhibitors that act as barriers to MNEs. We link out our findings with a number of propositions that we derive, which may be considered for implementation by MNEs and could help them endow their GVCs with resilience.

The purpose of this review paper is to address the need for mapping the thematic structure of fuzzy-set qualitative comparative analysis (fsQCA) in the context of tourism and hospitality research, in response to the growing interest in this methodology.

This study conducts a comprehensive systematic review using the SPAR-4-SLR procedure to produce a scientific map of top-tier research using the fsQCA technique in tourism and hospitality studies.

A major finding of this review investigation is the identification of six knowledge clusters: business competitiveness in the hospitality sector; psychoanalysis of tourist behaviour and satisfaction; entrepreneurship in the tourism and hospitality sector; tourism business ecosystem; sustainable tourism; and service quality in the tourism and hospitality sectors.

Although this review assessment relied heavily on articles published in prestigious journals, it does not rule out the idea that other sources, such as conference proceedings, can provide valuable insight.

Novel insights into the intellectual structure of tourism and hospitality research using the fsQCA technique, as well as ideas for future exploration in this domain, are presented in this review.

In an era marked by heightened geopolitical uncertainties, such as international conflicts and economic instability, the dynamics of energy markets assume paramount importance. Our study delves into this complex backdrop, focusing on the intricate interplay the between traditional and emerging energy sectors.

This study analyzes the interconnections among green financial assets, renewable energy markets, the geopolitical risk index and cryptocurrency carbon emissions from December 19, 2017 to February 15, 2023. We investigate these relationships using a novel time-frequency connectedness approach and machine learning methodology.

Our findings reveal that green energy stocks, except the PBW, exhibit the highest net transmission of volatility, followed by COAL. In contrast, CARBON emerges as the primary net recipient of volatility, followed by fuel energy assets. The frequency decomposition results also indicate that the long-term components serve as the primary source of directional volatility spillover, suggesting that volatility transmission among green stocks and energy assets tends to occur over a more extended period. The SHapley additive exPlanations (SHAP) results show that the green and fuel energy markets are negatively connected with geopolitical risks (GPRs). The results obtained through the SHAP analysis confirm the novel time-varying parameter vector autoregressive (TVP-VAR) frequency connectedness findings. The CARBON and PBW markets consistently experience spillover shocks from other markets in short and long-term horizons. The role of crude oil as a receiver or transmitter of shocks varies over time.

Green financial assets and clean energy play significant roles in the financial markets and reduce geopolitical risk. Our study employs a time-frequency connectedness approach to assess the interconnections among four markets' families: fuel, renewable energy, green stocks and carbon markets. We utilize the novel TVP-VAR approach, which allows for flexibility and enables us to measure net pairwise connectedness in both short and long-term horizons.

This study's aim was to investigate the role of the perceived values of gaming on consumers' perceptions of brands as cool as well as the impacts on the consumer–brand equity relationship. The study proposed a framework highlighting the influences of fashion-branded games on brand coolness and building fashion brands' overall equity. As significant factors affecting gamers, gender and gaming have been studied as moderators affecting the overall proposed framework.

A quantitative method was used to assess the significance of the relationships within the proposed model. Partial least squares structural equation modeling technique was implemented to assess the framework's relationships with a sample size of 248 active online gamers.

The findings indicate that brand equity is positively associated with perceived brand coolness. Furthermore, of the three core online game values, perceived enjoyment was most strongly associated with perceived brand coolness, with other values, such as self-expression and perceived emotional challenge, having a weaker association. The multigroup analysis results further suggest that in the fashion industry, building brand equity through online games is strongly related to perceived brand coolness among female respondents, with the role of perceived brand coolness affecting male respondents to a lesser degree.

The contribution of this study to the existing literature consists in providing a deeper understanding of the impact of branded games on fashion brands' overall equity. The results provide insights for fashion brand managers into the significant effect of fashion gaming collaborations on consumers' behavioral outcomes.

Under the background of continuous sluggishness of the real economy and expansion of asset sectors, the Chinese economy exists a trend of “from the real to the virtual.” Managing the corporate financialization is the key to prevent the real economy “from real to virtual.” The paper explores the influence of family involvement on corporate financialization since family firms are an important proportion of real sectors.

Based on Socioemotional Wealth Theory, this paper makes empirical study using the data of Chinese A-share listed companies from 2008 to 2022 to explore the influence of family involvement on corporate financialization, mainly from the perspectives of family engagement, family identity of CEO and family control power.

These are the findings: (1) Family engagement will inhibit corporate financialization; (2) Compared with employing external managers, family members acting as CEOs will decrease corporate financialization; (3) The proportion of family ownership is negatively correlated with the level of corporate financialization.

The originality of this paper include these: (1) Analyzing the differences in the financialization of real enterprises with different characteristics and attributes; (2) Expanding the research on the internal motivation of the financialization of the real enterprises, and supplementing the research literature on family firms and corporate financialization; (3) Exploring the internal influence mechanism of financialization of family firms under the background of Chinese culture.

Monetary policy has major impacts on macroeconomic indicators of the country. Accordingly, uncertainty regarding monetary policy shifts can cause challenges and risks for businesses, financial markets and investors. Thus, the purpose of this study is to investigate how real estate market volatility responds to monetary policy uncertainty.

The GARCH-MIDAS model is applied in this study to investigate the nexus between monetary policy uncertainty and real estate market volatility. This model was fundamentally instituted to accommodate low-frequency variables.

The results of this study reveal that increased monetary policy uncertainty highly affects the volatility in real estate market during the peak period of COVID-19 as compared to full sample period and COVID-19 recovery period; hence, a significant decline is evident in real estate market volatility during crisis.

This study is particularly focused on peak and recovery period of COVID-19 considering the geographical region of Greece, Japan and the USA. This study provides a complete perspective on the nexus between monetary policy uncertainty and real estate markets volatility in three distinct economic views.

The textile industry harms the environment at every stage of production, from the acquisition of raw materials to the disposal of finished products. It is very important for the textile industry to adapt to the basic policies on environmental sensitivity and sustainability to keep up with the transformation in production processes and the rapid changes occurring around the world in order to exist in global competition. Within the scope of sustainable development goals, it is of great importance to measure and evaluate indicators of all processes of the sector. This paper aims to present application of multi-criteria decision making (MCDM) methods for the assessment of sustainable development in textile industry.

The data of a multinational clothing company’s four-year sustainability performance between 2018 and 2021 were evaluated under 22 sustainability parameters determined using two new MCDM techniques, namely the combined consensus solution method and multi-attribute ideal real comparative analysis. In determining the criteria, priority key indicators were determined by taking into account the sector’s relationship with the environment, raw material consumption and social adequacy.

According to the application results of both methods, the year 2021 shows the best performance. It has been seen that the sustainability performance of the Inditex group has increased over the years and the results of the applied models support each other. It can be suggested that the proposed approach be applied to evaluate the progress in the textile sector with the relevant data on a particular company or on a macro scale.

This study makes an important contribution to the field in terms of the fact that the methods used are recent and have no application in the field of textiles. It allows the evaluation of different sustainability criteria together using a single method. It is very important to share data on sustainability indicators with customers, employees, suppliers, investors, partner organizations and society and evaluate performance. Analyzing sustainability performance on the basis of annual reports is important in terms of identifying good practices, sharing them with the community and setting an example. In addition, using scientific methods in the evaluation of the sustainability report data published by companies regularly provides significant feedback for policymakers and academics.

Industry 4.0 has received significant attention in today's competitive business market, necessitating a restructuring of functional domains in nearly every manufacturing organization. A comprehensive strategy to improve performance in preparation for Industry 4.0 implementation necessitates several steps, one of which is the establishment of performance outcomes (POs). The aim of this paper is to identify and rank the POs realized due to the adoption of Industry 4.0 enablers.

Based on an extensive literature review and inputs received from experts, a comprehensive list of enablers and the POs was prepared and finalized. This paper proposes a framework based on hybrid solution methodology, namely Neutrosophic Analytical Hierarchy Process (N-AHP) and Neutrosophic Combined Compromise Solution (N-CoCoSo), to rank the POs realized due to the adoption of Industry 4.0 enablers. The N-AHP methodology has been adopted to calculate the relative weights of the Industry 4.0 enablers. In comparison, the N-CoCoSo method has been adopted to rank the POs of Industry 4.0.

The proposed framework is applied to an Indian manufacturing organization to test the organization's practical applicability. Additionally, sensitivity analysis is also carried out to check the steadiness of the proposed framework. The findings of this study revealed that “Improved responsiveness to market conditions in today's competitive business environment” is the top-ranked PO of Industry 4.0, followed by “Enhanced competitiveness and better market share”, “Better product quality, through smart management of production process” and “Reduction in manufacturing waste and environmental sustainability” which could be realized due to adoption of its enablers.

This research would aid practitioners by enhancing the practitioners' capacity to understand and prioritize the various POs resulting from implementing Industry 4.0 enablers. Embracing a clear strategic plan will further assist practitioners in improving the efficiency of Industry 4.0 implementation.

Previous literature has only addressed the relationship between Industry 4.0 enablers and POs in a limited way. This paper attempts to compile a comprehensive list of Industry 4.0 enablers relevant to manufacturing organizations in order to fill this knowledge and research gap.

This study adopts the perspective of dynamic capabilities to investigate influencing factors and proposes improvement strategies of supply chain resilience of prefabricated construction.

The structural equation model (SEM) is used to identify and verify the relationship between factors influencing supply chain resilience of prefabricated construction from the perspective of dynamic capabilities. The system dynamics (SD) model is constructed to dynamically simulate the specific effects of different influencing factors.

Results indicate that: (1) An evaluation index system for supply chain resilience of prefabricated construction containing five first-level indicators and 36 second-level indicators is constructed; (2) Ability to anticipate, ability to respond, ability to adapt, ability to recover and ability to learn are positively correlated with the supply chain resilience of prefabricated construction and (3) ANT3 (information system), RES1 (quick response), ADA3 (buffer stock) and LEA4 (trust) are the most leading factors influencing supply chain resilience of prefabricated construction over time.

This study fulfills the need for an in-depth exploration of the various influencing factors on supply chain resilience of prefabricated construction from the perspective of dynamic capabilities. Furthermore, this study provides improvement strategies to enhance supply chain resilience of prefabricated construction in China.