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This study aims to examine how the initial ambiguity of COVID-19 contributed to tourists' intentions for visiting a once-viral outbreak site in the future.

The present study (N = 248) used partial least-squares structural equation modeling (PLS-SEM) to examine whether perceptions of ambiguity and mismanagement of COVID-19 are indirectly related to intentions to travel to Wuhan in a post-pandemic world through perceptions of risk and tourism value. Further, whether the model effects differed as a function of individual safety orientation was examined.

Perceptions of COVID-19 risk and tourism value serially mediated the effects of perceived COVID-19 ambiguity on post-pandemic travel intentions. Safety orientation did not moderate any paths. Perceived risk was a negative direct correlate of post-pandemic travel intentions.

The current study's strength is rooted in its specific targeting of post-pandemic travel intentions to Wuhan—the first city to experience a widescale outbreak of COVID-19 and subsequent international stigma—compared to general travel inclinations.

The purpose of this study is to check the impact of financial development on green technological innovation (GTI).

The sample size includes the 20-year (2001–2020) financial statistics of six Gulf Cooperation Council (GCC) region countries. To check the proposed relationship, this research uses a series of econometric models including fixed effect, fully modified ordinary least square and robust least square models.

The statistical results imply that financial sector development has a direct significant impact on GTI. A developed financial sector can uplift green technological development by offering more loans to industrial sectors and the import of modern technology. The statistical analysis further reveals the positive impact of gross domestic product (GDP), foreign direct investment inflow and trade volume while the negative impact of resources contribution on GTI.

The findings suggest key policy suggestions regarding the role of the financial sector in promoting GTI in the GCC region.

The novelty of this study lies in its examination of the relationship between FD and GTI in the GCC countries, a region with its unique economic and environmental dynamics.

Insufficient intra-organizational diffusion of prefabricated construction (PC) technology hinders its implementation benefits. More research on intra-organizational diffusion of PC technology is required to improve organizational performance in PC implementation. This study aims to explore the antecedents and consequence of intra-organizational diffusion of PC technology.

This study established an antecedent and consequence model of intra-organizational diffusion of PC technology from the perspective of contingency theory. The model was empirically tested by 91 valid questionnaires using partial least squares-structural equation modeling (PLS-SEM).

The results indicate that organizational support (OSU), organizational climate (OC) and mechanistic organizational structure (OST) positively influence intra-organizational diffusion of PC technology, which further positively influences organizational performance. The relationship between OC and intra-organizational diffusion of PC technology is mediated by OSU. Technological turbulence negatively moderates the relationship between OSU and intra-organizational diffusion.

This is the first paper to study the antecedents and consequence of intra-organizational diffusion of PC technology and an expansion of contingency theory in the research field of PC technology. This study helps to theoretically stimulate future research on intra-organizational diffusion and practically promote intra-organizational diffusion of PC technology along with improving organizational performance in its implementation.

In many of today’s manufacturing industries, such as automobile, aerospace, defence, die and mould making, medical and electrical discharge machining (EDM) has emerged as an effective material removal process. In this process, a series of discontinuous electric discharges is used for removing material from the workpiece in the form of craters generating a replica of the tool into the workpiece in a dielectric environment. Appropriate selection of the tool electrode material and combination of input parameters is an important requirement for performance enhancement of an EDM process. This paper aims to optimize an EDM process using single-valued neutrosophic grey relational analysis using Cu-multi-walled carbon nanotube (Cu-MWCNT) composite tool electrode.

This paper proposes the application of grey relational analysis (GRA) in a single-valued neutrosophic fuzzy environment to identify the optimal parametric intermix of an EDM process while considering Cu-MWCNT composite as the tool electrode material. Based on Taguchi’s L9 orthogonal array, nine experiments are conducted at varying combinations of four EDM parameters, i.e. pulse-on time, duty factor, discharge current and gap voltage, with subsequent measurement of two responses, i.e. material removal rate (MRR) and tool wear rate (TWR). The electrodeposition process is used to fabricate the Cu-MWCNT composite tool.

It is noticed that both the responses would be simultaneously optimized at higher levels of pulse-on time (38 µs) and duty factor (8), moderate level of discharge current (5 A) and lower level of gap voltage (30 V). During bi-objective optimization (maximization of MRR and minimization of TWR) of the said EDM process, the achieved values of MRR and TWR are 243.74 mm³/min and 0.001034 g/min, respectively.

Keeping in mind the type of response under consideration, their measured values for each of the EDM experiments are expressed in terms of linguistic variables which are subsequently converted into single-valued neutrosophic numbers. Integration of GRA with single-valued neutrosophic sets would help in optimizing the said EDM process with the Cu-MWCNT composite tool while simultaneously considering truth-membership, indeterminacy membership and falsity-membership degrees in a human-centric uncertain decision-making environment.

To address the challenges encountered in disaster responses, optimize resource utilization, minimize environmental and social impact, and ensure transparency and accountability, it is essential to review humanitarian supply chains and incorporate sustainability considerations. Humanitarian organizations can enhance their ability to deliver timely and effective assistance to those in need by continuously improving supply chain practices. Consequently, this work explores the convergence of two fast-growing domains: sustainability and humanitarian supply chain management (HSCM).

The authors conducted a systematic literature review of peer-reviewed articles to identify the prominent research trends and themes from the two domains' interactions. The extant literature is represented under the theory, context, characteristics, and research method (TCCM) framework. The authors have utilized a stakeholder theory perspective to identify coordination and collaboration among the various stakeholders.

This study's review findings reveal five future research directions formulating this study's central themes: the role of environmental sustainability, coordination, and collaboration in building effective HSCs; the role of humanitarian aid for the responsive HSC; the influence of big data predictive analytics on the HSC performance; development and empirical validation of sustainable HSC performance framework; the role of HSC stakeholders in building effective and efficient HSCs.

There is no existing academic literature review available on sustainable HSCM. This review fills this void by fostering discussion about sustainable humanitarian supply chains where the authors notably propose the TCCM framework in the context of sustainable HSCM, followed by a stakeholder network.

The existence of the advertising delay effect and its impact on supply chain operations have been demonstrated in the current study. Therefore, this study develops a timely inventory control strategy for the fresh produce supply chain to address the advertising delay effect in the fresh produce supply chain.

This study proposes a game model based on the Nerlove-Arrow time delay differential equation and Pontryagin's maximum principle. Through comparative analyses of the optimal equilibrium strategies, the authors compare the optimal equilibrium strategies, product goodwill and optimal inventory trajectories for suppliers and retailers under secondary replenishment decisions and decentralized decisions.

The authors find that (1) Only when the sales cycle meets certain conditions can the overall profit of the supply chain under the secondary replenishment decision be greater than that under the decentralized decision. As the price markup coefficient increases, the total profit of the supply chain first increases and then decreases. (2) With the increase in the delay time, the replenishment quantity during the initial period gradually decreases. After the delay time elapses, the inventory depletion rate under secondary replenishment decisions is faster than that under decentralized decision-making. (3) Although there is a continuously increasing maximum value of product goodwill with the increase in delay time, it becomes difficult to achieve this value for longer delays.

The authors’ findings provide a theoretical basis for supply chain members of fresh agricultural products to select replenishment and inventory control strategies when adopting different levels of delay in advertising marketing.

Firstly, this paper explains the impact of advertising delay effect on fresh produce supply chain from a dynamic perspective, and secondly, it provides guidance on advertising formulation and inventory replenishment for fresh produce retailers under the influence of advertising delay effect.

The main aim of this study is to explore the relationship between information system flexibility and dynamic capabilities to build sustainable and net zero supply chains under the influence of environmental dynamism.

We have formulated a self-administered survey, with 359 participants contributing responses. Prior to delving into foundational assumptions, such as homoscedasticity and normality, a nonresponse bias analysis was executed. The integrity of the data, in terms of reliability and construct validity, was gauged using confirmatory factor analysis. Subsequent regression outputs corroborated all the proposed assumptions, fortifying the extant scholarly literature.

The empirical findings of this research underscore a positive correlation between Information system flexibility, dynamic capabilities and a net zero supply chain, especially in the context of environmental dynamism. Data sourced from the cement manufacturing sector support these observations. We also found that environmental dynamism moderates the relationship between data analytics capability and sustainable supply chain flexibility but does not moderate the relationship between Resource flexibility and sustainable supply chain flexibility. Additionally, this research strengthens the foundational principles of the dynamic capability theory.

The conceptual framework elucidates the interplay between information system flexibility, dynamic capabilities, and sustainable supply chain flexibility, emphasizing their collective contribution towards achieving sustainable chain net zero, introducing environmental dynamics as a moderating variable that augments the scholarly discourse with a nuanced layer of analytical depth.

Project portfolio risk (PPR) management plays an important role in promoting the smooth implementation of a project portfolio (PP). Accurate PPR prediction helps managers cope with risks timely in complicated PP environments. However, studies on accurate PPR impact degree prediction, which consists of both risk occurrence probabilities and risk impact consequences considering project interactions, are limited. This study aims to model PPR prediction and expand PPR prediction tools.

In this study, the authors build a PPR prediction model based on a genetic algorithm and back-propagation neural network (GA-BPNN) integrated with entropy-trapezoidal fuzzy numbers. Then, the authors verify the proposed model with real data and obtain PPR impact degrees.

The test results indicate that the proposed method achieves an average absolute error of 0.002 and an average prediction accuracy rate of 97.8%. The former is reduced by 0.038, while the latter is improved by 32.1% when compared with the results of the original BPNN model. Finally, the authors conduct an index sensitivity analysis for identifying critical risks to effectively control them.

This study develops a hybrid PPR prediction model that integrates a GA-BPNN with entropy-trapezoidal fuzzy numbers. The authors use this model to predict PPR impact degrees, which consist of both risk occurrence probabilities and risk impact consequences considering project interactions. The results provide insights into PPR management.

Informed by the resource-based view of the firm, dynamic capabilities theory and contingency theory, this study examines the impact of Industry 4.0 (IR4.0) technologies adoption on firm performance (FP) while accounting for the mediating role of innovation ambidexterity (IA) and moderating roles of contextual and methodological factors that drive the performance gains of the phenomenon.

A random-effect model in comprehensive meta-analysis (CMA) is used to synthesize 113 studies in 115 independent samples with 192,188 observations.

This analysis demonstrates that IR4.0 digital technologies are directly related to financial and non-financial performance, disclosing that the performance effect on non-financial is the largest. Moreover, there is a complementary partial mediation role of the impacts of IR4.0 on FP by IA. Furthermore, this focal relationship is moderated by boundary-spanning conditions: contextual factors – firm size, business type, economic development, industry sector and methodological factors – proxy of FP, sample size and study type.

The results imply that IR4.0 produces financial and non-financial benefits by enabling firms to develop dynamic capabilities like innovation ambidexterity, which informs managers and practitioners that unless IR4.0 technologies and IA strategies are combined together to generate superior FP, IR4.0, in and of itself, would produce a less positive impact on FP than the combined impact of IR4.0 and IA. Therefore, managers should focus on converting IR4.0 resources to dynamic capabilities like IA by leveraging open innovation strategies or building IR4.0-based coordination mechanisms by creating cross-unit business synergies.

To the best of the authors' knowledge, per the literature review, this is the first meta-analysis structural equation modeling study on the interplay between IR4.0, innovation ambidexterity and firm performance.

Integrating transaction costs economics and task-technology fit theory, this study distinguishes two categories of social media–enabled interactions, namely task-related interactions and tie-related interactions, and explores the match between these two and firms' use of contracts in achieving safeguarding and coordinating purposes in interfirm governance.

Two studies were conducted to test the hypotheses. In Study 1, this study collaborated with a professional market research firm and collected responses from Chinese manufacturing firms in a survey. In Study 2, this study designed a scenario-based experiment and collected 239 participants from the Credamo platform.

This study categorized social media–enabled interactions into task-related interactions and tie-related interactions and conducted two studies to reveal that the safeguarding purpose of contract specificity is amplified by tie-related interactions, whereas the coordinating purpose of contract specificity is strengthened by task-related interactions.

This study assumes that firms permit and encourage the use of social media. However, some firms might prohibit the use of social media due to risk issues, or their partners may be prohibited from using social media.

Given that social media–enabled interactions have joint effects with contracts in achieving safeguarding and coordinating purposes, a firm's employees should match their goals with an appropriate type of social media–enabled interactions.

This study enriches the interfirm governance literature by uncovering the roles of these two types of interactions in matching contract specificity to achieve safeguarding and coordinating purposes, which provides actionable insights for managers in governing interfirm relationships.