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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.

This empirical study aims to examine luxury fashion retailers' localised multiple channel distribution strategies in China.

Through case studies of 15 participating retailers, qualitative data were collected from 33 semi-structured interviews.

Strong impacts of internationalisation strategies, distribution strategies and channel length towards multiple channel retailing are revealed. Multi-channel retailing is widely employed by firms who have entered China and further developed their businesses through local partnerships and adopted a selective distribution strategy via relatively longer channels. Omni-channel retailing is only suitable for the few retailers using an exclusive distribution strategy through direct marketing and wholly owned customer relationship management. As a dynamic transformation from multi- to omni-channel retailing, cross-channel retailing is adopted by those who are withdrawing from local partnerships and shifting to wholly owned expansions and operations in host markets.

The results are potentially challenged by relatively small sample size.

Practitioners are suggested to adapt multiple channel retailing to their international expansion strategies, distribution strategies and channel length in the host markets.

This paper contributes to the literature in both multiple channel retailing and international retailing by offering insights into the motives, development patterns and suitability of multiple channel retailing in the international retail marketing context.

This study aims to review the prepositioning of relief items literature through a decision-making lens to explore the decisions involved, the factors guiding them and the influence of model design on these decisions. Despite their potential to inform decision-making, quantitative prepositioning models remain underutilised in practice. Understanding the foundational principles that shape model design and their connections to decision-making is crucial for effectively developing and implementing more practical models.

A systematic literature review was conducted, and 97 relevant papers were analysed bibliographically and thematically. The thematic analysis is guided by the value-focused thinking approach, which provides a structured understanding of the decision-making process by focusing on the decision makers’ values.

This study identifies key prepositioning decisions related to facilities, inventory and distribution. It highlights efficiency, effectiveness and equity as the main values guiding prepositioning decisions and examines the mutual influence of model design and decisions. Moreover, a decision-making framework for prepositioning problems has been developed, outlining key steps and relevant decisions.

This research provides novel insights into how the decision-making process regarding prepositioning is reflected in quantitative models. It helps researchers choose model designs that better align with decision makers’ priorities and requirements, increasing the models’ practicality. Additionally, it helps decision makers comprehend quantitative models and the reasons behind their mathematical complexities, ultimately improving the effectiveness of decision-making for prepositioning.

The critical chain project buffer monitor process addresses uncertainty and variability in project duration. However, classical buffer monitor methods only consider buffer consumption, while the dynamic allocation of buffer zones and the buffer consumption trend of activities are ignored. This paper presents the innovative framework for dynamic monitoring of project buffer which covers the dynamic buffer allocation, predictive analytics of buffer utilization and a new monitoring technique based on control chart graph.

First, a dynamically buffer allocation model is framed, and buffer zones are given to the activities considering risks. Then, a predictive model amalgamating Bayesian Optimization, Convolutional Neural Networks, and Long Short-Term Memory networks (BO-CNN-LSTM) is framed. Finally, a new buffer monitor framework is constructed that takes into account historical information about buffer usage and utilizes two thresholds derived from control chart theory.

This approach is empirically tested on a representative agricultural website project in China. The results show that, first, the dynamic buffer allocation makes better use of the project buffer, reduces buffer waste and increases the possibility of timely completion of the project. Second, the BO-CNN-LSTM model predicts better than Long Short-Term Memory (LSTM) and Grey Neural Network Model (GNNM), providing project managers with new management insights and perspectives. Third, the novel monitoring procedure makes the leveraging of historical data possible in the control of the schedule deviations, allowing for more timely interventions in the course of the implementation of the project.

A new project buffer monitoring method suitable for uncertain project environments is proposed.

Based on imprinting theory and episodic future thinking, this paper aims to study how CEOs’ attributes and experiences inform innovation in tourism and hospitality businesses. It also explores ways to quantify innovation in this sector.

The authors quantitatively analysed innovation in tourism and hospitality using extensive data from companies’ annual reports. They further adopted multivariate regression to test how CEOs’ experience affects enterprise innovation.

Results demonstrate that CEOs’ academic education and rich work experience can promote corporate innovation. The authors also identified a mediating role of the tone of narrative disclosure in annual reports between CEOs’ academic education and corporate innovation. The imprinting effects of career experience and educational experience appear both independent and interactive.

CEOs are more inclined to engage in corporate innovation when influenced by the combined imprinting effects of strategic management training and work experience. Additionally, leaders should consider how communication styles indirectly influence innovation activities.

This paper introduces an integrated perspective that blends imprinting theory and episodic future thinking to bridge knowledge gaps regarding the interaction of CEOs’ past experiences. This work enhances understanding of how CEOs’ imprinted experiences, together with their capacity for envisioning future scenarios, can drive corporate innovation.

This study aims to clarify the influence of different CEO’s political orientation (liberal/conservative) and corporate political activity on ESG performance, considering contingencies related to CEO attributes and corporate governance mechanisms.

Using a sample of 131 companies from the Standard and Poor’s 500 index, this study employs fuzzy-set Qualitative Comparative Analysis (fs/QCA) to analyze combinations of conditions (i.e. configurations) that lead to greater ESG (i.e. environmental, social, and governance) performance.

Drawing on the upper echelon theory and the theory of social exchange, the findings show that different CEO’s political orientation (liberal/conservative) can contribute to ESG performance, depending on the combination of conditions. Furthermore, the results emphasize the importance of corporate political activity as a core condition to enhance ESG performance.

Taking a configurational approach, this study explores combinations of conditions that explain ESG performance, including CEO’s political orientation and corporate political activities as antecedent conditions. Unlike past research, this study examines possible complementarities between these two conditions and assumes that different CEO’s political orientation can have a positive influence on ESG performance, depending on the combination of conditions.

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.

Societal response to COVID induced many changes in the way we now live. Air transportation was one of the more visible “victims” of COVID response, with several major airlines declaring bankruptcy and others downsizing to a degree not seen previously. In spite of these shocks, the international air cargo sector carried on. Anecdotal evidence suggests airlines that either specialized in cargo or in turn were able to adjust their fleets to carry more cargo (including better utilization of existing backhauls) were best able to weather the pandemic. To explore this issue further, we examine detailed international air passenger and cargo traffic data (both fronthaul and backhaul) from the US Bureau of Transportation Statistic's TranStats database before and during COVID to elucidate how the pandemic affected air carrier operations at a time of great uncertainty. Better operational flexibility seems to have been critical to success during COVID. To this end, we find that many Asian-based carriers were superior at adjusting to the new cargo refocused reality of COVID operations, while their US-based counterparts lagged substantially behind. We speculate on potential reasons for this difference and also what our findings might mean for industry investment moving forward.

The study aims to investigate how artificial intelligence (AI)-powered virtual streamers can supercharge brands in live-streaming virtual commerce (v-commerce). Built upon social identity theory (SIT) and experiential value theory, we developed a framework to investigate the impact of AI-powered virtual streamers’ personalization and human-like personalities and live-streaming v-commerce’s system quality and content quality on brand image, mediated by parasocial interaction and experiential value.

A survey was designed and distributed to the target respondents via social media channels. SmartPLS version 4.0.9.4 was used to analyze a total of 354 responses after the data were obtained via purposive sampling.

The results show that personalization, human-like personality, system quality and content quality are positively associated with parasocial interaction and experiential value, which subsequently impact brand image.

This study addresses the gap of relatively sparse academic literature on the implications of AI-powered virtual streamers in live-streaming v-commerce on brand image.

This study explores the relationship between state ownership and labour cost stickiness across strategic and non-strategic industries in developing economies. It aims to uncover how non-economic considerations and sociopolitical objectives influence cost behaviour in state-owned enterprises (SOEs), particularly within strategic sectors.

The research employs data from 151 firms listed on the Tehran Stock Exchange from 2011 to 2021. Using multiple linear regression analysis with year and industry-fixed effects, the study investigates the impact of state ownership on labour cost stickiness, considering the moderating role of industry type.

The analysis reveals a significant influence of industry type on the relationship between state ownership and labour cost stickiness. SOEs exhibit higher labour cost stickiness, especially in strategic industries subject to greater public scrutiny and government intervention. These findings align with agency theory, highlighting how sociopolitical pressures shape SOEs’ managerial decisions and cost management strategies.

This research fills a crucial gap in the literature on cost behaviour in developing countries, emphasising the importance of industry-specific strategies in mitigating labour cost stickiness in SOEs. It provides new insights into how state ownership and sociopolitical objectives affect cost management, offering valuable implications for policymakers and managers in similar economic contexts.