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It is found that previous studies only focus on how digital transformation contributes to individual firms’ green innovation performance while ignoring the important role that it plays in the spillover and diffusion of green innovations among peer firms. Therefore, this study aims to investigate the influence of focal firms’ digital transformation on the spillover of green innovation among peer firms in heavily polluting industries mediated by environmental, social and governance (ESG) performance and agency conflict. Further, this study is also expected to explore the effects of digital transformation’s green innovation spillover.

This study chooses 6,438 A-share heavily polluting listed firms in the stock exchanges based in Shanghai and Shenzhen in China during 2010–2020 as samples and tests the hypothesis with ordinary least squares (OLS) regression. Results prove to be robust to a battery of robustness analyses the authors performed to take care of endogeneity.

The results show that the focal firm’s digital transformation may trigger their peer firms’ green innovation spillover and prompt them to engage in green innovation activities actively. The mechanism test shows that peer firms’ ESG performance and agency conflict mediate the influence path between digital transformation and peer firms’ green innovation spillover. Finally, among heavily polluting firms with high industry competition and large scale, digital transformation’s green innovation spillover effects are more significant in conventional energy-based source control, end-of-pipe treatment and substantive green innovation.

This study is possible to provide a potential driving mechanism of green innovation spillovers. The findings lay a sound foundation for future research, providing important theoretical support and practical insights for digital transformation to empower heavily polluting industries to achieve green transformation and low-carbon development.

The link between interlocking directors and mergers and acquisitions (M&A) efficiency has been analyzed in an information asymmetry environment. Despite an abundance of evidence highlighting that interlocking directors do contribute to M&A efficiency in an acquirer-target binary relationship, the target is embedded in a complex network of supplier-customer relationships, which implies that the acquirer needs to consider the value of suppliers, distributors and retailers in the target’s supply chain in improving M&A efficiency. Through the lenses of acquirer-target multivariate relationships, this paper aims to examine how directors with supply chain experience (DSCs) act as heterogeneous network pipes to affect M&A efficiency.

Using a sample of 311 A-share listed firms on the Shanghai and Shenzhen stock exchanges in China during 2011–2020, this paper investigates the relationship between DSCs and M&A efficiency by using ordinary least squares (OLS) regression.

Through empirical research, we verify a negative relationship between DSCs and M&A duration and an inverted U-shaped relationship between both DSCs and M&A performance, revealing the complexity of the relationship between experience and efficiency. Furthermore, drawing on upper echelon theory, the information value of DSCs will be greatly reduced when executives have overconfident psychological characteristics, which are mainly shown to negatively moderate the relationship between DSCs and M&A performance. We also conduct multiple robustness tests and supplemental analyses to illustrate the robustness and boundaries of our findings. Finally, DSCs are likely more important in environments among growth and mature firms as well as high-growth industries.

We break through the assumption that interlocking directors contribute to M&A efficiency in an acquirer-target binary relationship and examine the impact of DSCs on M&A efficiency based on micro-empirical evidence from the value of target-related upstream or downstream industries, which extends the connotation of interlocking directors and enriches the study related to factors influencing M&A efficiency.

Tourism value chain (TVC) analysis has been widely used as an alternative approach for designing sustainable and inclusive programs for tourism development in Africa, Asia, and the Pacific. This chapter looks at the experiences of three sustainable tourism initiatives in the Philippines to assess the strengths and limitations of the value chain as a framework for destination development. Short case studies describe the experiences of stakeholders in two popular destinations in the Philippines: the surfing town of San Juan, La Union, and the resort-island of Panglao, Bohol. The third case study shares the perspective of the Transforming the Tourism Value Chain (TTVC) project, a national campaign for more sustainable hotels, resort as well as meetings, conventions, incentives, and event (MICE) facilities in various destinations around the country. Stakeholders deeply involved in implementing these projects share their insights on the successes, challenges, and limitations of TVC-based approaches to resilient and sustainable destination development. The destinations' experiences suggest that the advocacy for sustainable management and operations may be comparable to a process of technology adoption or acceptance along the TVC. Practical and theoretical recommendations for leveraging the TVC toward more holistic and sustainable visitor economies are given at the end of this chapter.

With the rapid development of society, major emergencies occur frequently, posing a serious threat to people’s lives and property. This study focuses on the chain reaction of major emergencies, aiming to improve the overall situational awareness and capabilities for managing major emergencies in complex scenarios.

We proposed an information support framework for the chain reaction of major emergencies based on a causality eventic graph (CEG). The framework consists of three modules: the data layer, the analysis layer and the service layer. The data layer focuses on the perception and collection of major emergency information. The analysis layer includes key components such as causality recognition, causality extraction, event fusion and generalization. In this layer, we developed several deep learning (DL)-based models using a joint extraction approach to obtain causal pairs. The service layer depicts the event evolution logic from both industry and public perspectives.

The empirical study has demonstrated the feasibility and effectiveness of the proposed information support framework. First, the BERT-BiLSTM-CRF model achieved the best performance in the causality extraction task. Second, the SBERT model was found to be more suitable for event fusion. Third, the analysis results of CEG revealed that the impact of pandemics on industries in turn affects other industries as well as people’s livelihoods and vice versa. The framework shows a better information support, discovery and reasoning effect. This study, however, still has several limitations. We focused primarily on causal logic and did not fully explore other logical relationships. In future work, we will incorporate more logical relations to further refine the eventic graph (EG).

This study proposes a novel information support framework for the chain reaction of major emergencies, leveraging CEG to provide targeted and hierarchical information to industry and public stakeholders. It solves several problems in the emergency management of major emergencies.

The objective of this study is to accurately predict the cost of green buildings to provide quantifiable criteria for investment decisions from investors.

This study proposes a hybrid prediction model ML-based for cost prediction of GBPs and obtains prediction parameters (PPs) associated with project characteristics through data mining (DM) techniques. The model integrates a principal component analysis (PCA) method to perform parameter dimensionality reduction (PDR) on a large number of raw variables to provide independent characteristic terms. Moreover, the support vector machine (SVM) algorithm is improved to optimize the prediction results and integrated with parameter dimensionality reduction and cost prediction.

The prediction results show that the mean absolute and relative errors of the hybrid prediction model proposed in this study are equal to 39.78 and 0.02, respectively, which are much lower than those of the traditional SVM model and MRA prediction model. Moreover, the hybrid prediction model with parameter dimensionality reduction also achieved better prediction accuracy (R² = 0.319) and superior prediction accuracy for different cost terms.

Theoretically, the hybrid prediction model developed in this study can reliably predict the cost while accurately capturing the characteristics of GBPs, which is a bold attempt at a comprehensive approach. Practically, this study provides developers with a new ML-based prediction model that is capable of capturing the costs of projects with ambiguous definitions and complex characteristics.

This study aims to examine the language choices of outdoor signs and menus in addition to the functions of outdoor signs in restaurants in a Saudi tourist city, Abha. The primary focus is on identifying the extent to which outdoor signs accurately represent the language choices of restaurant menus.

The study developed a conceptual framework for the linguistic landscape (LL) of restaurants. It employed a quantitative approach to collect outdoor signs and menus of 75 sampled restaurants in Abha using online photos and a smartphone camera. Then it analyzed the frequency and percentage of language choices on outdoor signs and menus as well as the extent to which language choices of outdoor signs represent menus.

The findings indicate that more than half (58.66%) of the restaurants employ bilingual signage in both Arabic and English. Other languages like Spanish, French, Chinese and Turkish are sporadically used, with multilingualism observed only in isolated instances. The study also reveals that bi/multilingualism on outdoor signs primarily serves informational purposes, where more than one-third (36%) of the outdoor signs use languages other than Arabic to serve a symbolic function. Regarding menus, Arabic and English dominate, while Turkish appears on one menu. Spanish, French, and Chinese are absent from restaurant menus, indicating linguistic mismatch in terms of language choices.

This study contributes to LL studies of restaurants in tourist cities by showing language choices and functions of outdoor signs and their alignment with menus.

The purpose of this study is to investigate the influence of ambidextrous strategy on supply chain resilience and its impact on firm performance, employing the Dynamic Capabilities View.

Through a survey of 215 supply chain professionals, the research employs a structural equation modeling analysis to examine the relationships between ambidexterity, agile operations, resilience, and performance.

The findings demonstrate that the ambidextrous strategy significantly enhances both agile operations and supply chain resilience. In turn, agile operations and resilience positively impact firm performance. The study also reveals that agile operations and supply chain resilience partially mediate the relationship between ambidextrous strategy and firm performance.

This research contributes to the supply chain management literature by highlighting the importance of an ambidextrous approach in fostering agile operations and resilience, thereby improving firm performance. It extends the dynamic capabilities view framework by elucidating how ambidexterity acts as a pivotal mechanism for adapting to disruptions and securing competitive advantage in volatile markets. Finally, measurements of ambidextrous strategy and resilience are provided to further enhance practitioners’ understanding of building these important components in networks.

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.

The purpose of the present paper is to analyse the impact of entrepreneurial orientation (EO) and customer orientation (Co.) on innovation in the restaurant industry, as well as how innovation also positively influences financial and market performance. Likewise, it is analysed whether human capital (HC) and competitive strategy (CS) have a moderating effect between innovation and performance.

To reach the stated goals, a survey was applied to 129 entrepreneurs in the restaurant industry in Baja California, Mexico and using partial least squares structural equation modelling, the research hypotheses were verified.

Results indicate that EO and Co positively influence innovation, which also furthers better financial and market firm performance; however, no moderating effect was found for HC nor CS.

The findings allow contributing from a practical-entrepreneurial standpoint, as it raises awareness about the importance of developing strategies that allow efficiently gaining knowledge to encourage a culture in the restaurant industry focused on EO and Co, which, for their part, will boost the design and implementation of innovations.

The paper contributes to understanding the behaviour of HC and CS, which may have an influence or not, depending on the role they have within a system.

This paper contributes to raising awareness of the importance of developing strategies that allow efficient knowledge to foster a culture in the restaurant industry focused on entrepreneurship and clientele.