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This study aims to investigate how firms of different sizes respond to competitive pressure from peers.

This study employs machine learning techniques to measure competitive pressure based on management discussion and analysis (MD&A) documents and then utilises the constructed pressure indicator to explore the relationship between competitive pressure and corporate risk-taking behaviours amongst firms of different sizes.

We find that firm sizes are positively associated with their risk-taking behaviours when firms respond to competitive pressure. Large firms are inclined to exhibit a high level of risk-taking behaviours, whereas small firms tend to make conservative decisions. Regional growth potential and institutional ownership moderate the relationships.

Utilising text mining techniques, this study constructs a novel quantitative indicator to measure competitive pressure perceived by focal firms and demonstrates the heterogeneous behaviour of firms of different sizes in response to competitive pressure from peers, advancing research on competitive market pressures.

Although environmental pressures have been covered in great detail in prior literature as the drivers of eco-innovation, there remains inconsistency in the empirical results concerning the effects of these pressures on eco-innovation behaviour. Hence, this paper aims to investigate the impact of environmental pressures, namely, regulatory pressure, green demand and competitive pressure, on eco-innovation among manufacturing SMEs. Moreover, it examined the mediating role of environmental capabilities on the environmental pressure–eco-innovation relationship.

Quantitative data were collected using an online self-reported questionnaire survey to test the hypothesised model. A total of 183 valid questionnaires were collected from managers and owners of manufacturing SMEs in Egypt.

The results of the data analysis using the Smart-PLS software package revealed that among environmental pressures, only green demand had a direct effect on eco-innovation. In addition, environmental capabilities only mediated the effect of competitive pressure on eco-innovation.

This study has been one of the few addressing the issue of how the drivers of eco-innovation interact. It has also provided the managers and owners of SMEs and policymakers with practical implications.

Due to the current pandemic, the importance of logistics functions and decisions is well understood both at the level of companies and users. Logistics systems and related decisions are of vital importance in making supply chains effective, efficient and without disruption. Logistic pressure factors may emerge at different points along the logistics process, and given the role of logistics decisions as one of the important indicators of competitiveness, the determination of the logistics pressures that are likely to increase the costs of business, and their causative factors are a vital aspect of the logistics decision-making process. The study aims to provide assistance in the selection of the most ideal logistics decision by ranking the pressure factors affecting the logistics system, especially during the pandemic period for logistics enterprises operating in Ordu and Giresun provinces and which have a corporate identity.

In this study, it is aimed to make the most ideal logistics decision selection by ranking the pressure factors affecting the logistics system, especially during the pandemic period for the logistics enterprises operating in Ordu and Giresun provinces and having a corporate identity. For that purpose interval-valued Pythagorean fuzzy (IVPF)–analytic hierarchy process (AHP) based combinative distance-based assessment (CODAS) methodology was used. Additionally sensitivity and comparison analysis were discussed.

Competitive pressure was found as the most important pressure factor affecting the logistics system during the pandemic period. Change in regulatory rules was the pressure factor found to have the least effect on the logistics system. Using the weights of logistics pressure factors, “Operational Decisions” was found to be the most ideal logistics decision selection.

The findings provide support for the evaluation of logistical pressures and decision options by presenting a decision model capable of processing ambiguous information. During a pandemic or similar period, the study assists decision makers in determining a new route. The findings will also call business managers' attention to logistical pressure factors and lead them toward more realistic and feasible practices in the logistics decision-making process.

This study provided an effective and applicable solution to a decision-making problem in the logistics sector including logistics pressure factors and the selection of logistics decisions. In this context, a methodology was presented that will allow businesses to self-evaluate their own logistics pressure factors and the selection of optimal solutions.

In the era of digitalization, digital technology has transformed businesses and created enormous opportunities for organizations worldwide. Unsurprisingly, research on digital transformation has garnered significant interest among academics in recent decades. However, this study aims to recognize the key and holistic antecedents influencing digital transformation in manufacturing firms. This study also investigates the indirect relationships of antecedents with firm performance.

The hypothesis was investigated using the partial least squares structural equation modeling (PLS-SEM) approach. The data was collected from 279 employees through a self-administered survey of manufacturing firms.

The results described a significant and positive impact of competitive pressure, leadership role, organization culture, organization mindfulness, government regulation, and IT readiness on digital transformation and firm performance. Furthermore, digital transformation partially mediates the relationship between antecedents and firm performance.

The study finds a holistic perspective of the critical antecedents of digital transformation using the mediation role of digital transformation and moderating effects of firm agility. Additionally, all antecedents have a significant association with Firm Performance.

Understanding the adoption of m-commerce in small and medium-sized enterprises (SMEs) is critical for their sustainable development. This study aims to investigate the adoption of m-commerce in Vietnamese SMEs, leading to the identification of the critical determinants and their relative importance for m-commerce adoption.

An integrated model is developed by combining the diffusion of innovation theory and the technology–organization–environment framework. Such a model is then tested and validated using structural equation modeling and artificial neural networks in analyzing the survey data.

The study indicates that perceived security is the most critical determinant for m-commerce adoption. It further shows that customer pressure, perceived compatibility, organizational innovativeness, perceived benefits, managers’ IT knowledge, government support and organizational readiness all play a critical role in the adoption of m-commerce in Vietnamese SMEs.

The findings of this study can lead to the formulation of better strategies and policies for promoting the adoption of m-commerce in Vietnamese SMEs. Such findings are also of practical significance for the diffusion of m-commerce in SMEs in other developing countries.

To the best of the authors’ knowledge, this is the first attempt to explore the adoption of m-commerce in Vietnamese SMEs using a hybrid approach. The application of this approach can lead to better understanding of the relative importance of the critical determinants for the adoption of m-commerce in Vietnamese SMEs.

This study intends to investigate drivers and consequences of supply chain coordination (SCC) towards green to highlight some convincing evidence for an emerging country's exporters to promote sustainable coffee development.

Data were gathered from surveying 189 managers of coffee exporters in Vietnam and then applied PLS-SEM for analysis.

This study demonstrates that top management sensitivity, along with institutional forces of regulation, market and competition, strongly stimulate exporters' supply chain coordination towards green. Additionally, that coordination boosts the export financial and market performance.

The findings may not be generalizable because the current study only included data from Vietnamese coffee exporters.

This study contributes to the current literature by looking from the perspective of coffee exporters – leading players in supply chains for export. The research findings represent the first solid argument for Vietnam coffee exporters to encourage SCC towards green and reveal several implications for managers and policymakers to support sustainable development in an emerging country.

With the change in climate and increased pollution, there has been a need to reduce environmental carbon emissions. This research aims to develop a framework for reducing environmental carbon footprints to improve business performance.

This study uses Scientific Procedures and Rationales for the Systematic Literature Reviews (SPAR-4-SLR) approach. Articles are searched in the Scopus database using various keywords and their combinations. It resulted in 651 articles initially. After applying different screening criteria, 61 articles were considered for the final study.

This study provided four themes and sub-themes within each category. This research also used theories, methodologies and context (TMC) framework to provide future research questions. This study used the antecedents, decisions and outcomes (ADO) framework for synthesising the findings. The ADO framework will help to achieve carbon neutrality and improve firms' supply chain (SC) performance.

This study provides theoretical implications by highlighting the various theories that can be used in future research. This study also states the practical implications for the achievement of carbon neutrality by the firms.

This study contributes to the literature linking carbon neutrality with business performance.

This study responds to the calls from the literature on identifying interactions among the sustainable supply chain management (SSCM) drivers, which influence focal firms’ SSCM decisions. It also determines how the effect of SSCM drivers differs across the upstream and downstream supply chains (SCs) entities of fast-moving consumer goods (FMCGs) companies.

We employ a multi-method design encompassing three studies: study 1 (multiple-case study), study 2 (quantitative survey), and study 3 (multiple-criteria decision-making or MCDM modeling).

The results show that the external drivers such as customer pressure, competition, and supplier pressure and internal drivers such as top management commitment interact to influence the adoption of SSCM practices, and this interaction is diverse across upstream and downstream SC entities of the FMCG sector. The study provides empirical evidence of relationships among the SSCM drivers, which influence SSCM decisions.

Understanding these interactions will help managers derive strategies to manage the overall SSCM ecosystem and recognize the multiplier effects of upstream to downstream and vice versa.

This study evaluated the determinants of augmented reality (AR) adoption in Malaysia's travel and tour operator sectors through an integrated technology-organization-environmental (TOE) and diffusion of innovation (DOI) model.

The TOE and DOI were considered the primary theoretical models but are combined and extended by including few additional variables. Data were collected from 220 respondents of travel and tour operating businesses in Malaysia and analyzed by applying PLS structural equation model technique.

The empirical results established that perceived cost, relative advantages, complexity and compatibility, observability, competitor pressure, value alignment, customer pressure, and trialability are positively connected with the behavioral intention except for external support. The results reveal that value alignment partially mediates the association between relative advantages and behavioral intention, complexity and behavioral intention, compatibility and behavioral intention, perceived cost and behavioral intention except in between trialability and observability.

This research is unique as the value alignment construct is included in the model, and thus it fulfills the literature gap by adding the mediation construct. This study contributes to enhancing AR's understanding of the Malaysian travel and tour operator industry through the lenses of owners or managers. It offers an integrated model that combines the TOE and DOI models, rare in this sector, and can be replicated or extended with validated scales.

Limited use of Internet of Things (IoT) technology on construction sites has restricted its value in the construction industry. To propel its widespread application, this paper explores the influencing factors and action paths of construction companies' IoT technology adoption behavior.

First, literature research, technology adoption theories, and semi-structured expert interviews were employed to build the adoption model. Second, a questionnaire survey was conducted among Chinese construction contractors to collect empirical data. Third, the structural equation model method and regression analysis were used to test the adoption model. Finally, the findings were further validated with interviews, case studies, and field observations.

External environmental pressure (EEP), perceived benefit (PB), top management support (TMS), company resource readiness (CRR), adoption intention (AI), and perceived compatibility (PCA) have a direct positive impact on adoption behavior (AB). In contrast, perceived cost (PC) and perceived complexity (PCL) exert a direct negative impact on AB. The EEP, PB, and PC are critical factors affecting AB, whereas AI is strongly affected by CRR and TMS. Besides, AI plays a part mediating role in the relationship between seven factors and AB. Company size and nature positively moderate AI's positive effect on AB.

This paper contributes to the knowledge of IoT technology adoption behavior in the construction sector by applying the technology adoption theories. Exploring the implementation barriers and drivers of IoT technology in construction sites from the perspective of organizational technology adoption behavior and introducing moderating variables to explain adoption behavior are innovations of this paper. The findings can help professionals better understand the IoT technology adoption barriers and enhance construction companies' adoption awareness, demand, and ability. This work also provides a reference for understanding the impact mechanism of the adoption behavior of other innovative technologies in construction.