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The authors empirically examined the theoretically recognized industrial linkages between manufacturing and services from the trade perspective. In particular, they confirmed the trade effect of manufacturing on services, given that global value chain fragmentation pervades and splits manufacturing and services segments separately in developed and developing countries.

Based on observations of 47 countries with manufacturing and service trade data from 1990 to 2020 and with gravity model specification, the authors primarily used the Poisson pseudo-maximum likelihood (PPML) estimation with multiple levels of fixed effects. Considering that many zero values are included in the dependent variable and potential endogeneity, other methods such as Tobit regression, Heckman estimation and two-stage least squares estimation (2SLS) are used. Subsample estimation also supplemented the empirical research.

The results showed that manufacturing trade is a stepping-stone rather than an obstacle to service trade. This finding exhibited significant robustness under different model specifications, instrumental variable estimation and subsample checks. Moreover, in contrast to the north–north country ties, manufacturing trade between northern and southern countries has played a prominent stepping-stone role; meanwhile, manufacturing trade among core–peripheral countries has a considerably more significant impact than the outcomes of core–core and peripheral–peripheral countries.

The authors provided direct clarification and revealed that trade in manufacturing remains the demand basis for service trade. As trade in manufacturing and services are typical phenomena of transnational production linkages, the authors suggested exploring the underlying role of global value chain (GVC) fragmentation and the offset and even barrier effect of biased institutional arrangements on GVC fragmentation.

This study explores the impact of packaging images (ingredients vs finished products), degree of food readiness (ready-to-heat vs ready-to-cook) and purchasing motivations (utilitarian vs hedonic) on consumer preferences.

Two 2 × 2 between-subject experiments were conducted to investigate the interactive effects of package image type and food readiness (Study 1) as well as their individual impacts (Study 2). Data analysis and hypothesis testing were performed using SPSS software.

Consumers initially preferred packaging images of finished products over ingredients when selecting ready-to-eat foods. However, their attitudes declined upon learning about specific food content. When motivated by hedonic factors, consumers favored images of finished products for ready-to-cook foods, whereas utilitarian motivations led to a preference for ingredient images. After purchasing, ingredient images were favored across both motivational contexts.

Food packaging images serve as crucial cues in consumer purchase decisions, though no consensus currently exists on whether these images should feature ingredients or finished products. This study offers valuable insights into how these visual factors affect consumer behavior and decision-making, providing manufacturers with guidance on enhancing product evaluations by consumers.

Firms are increasingly digitalizing their business processes and expanding them into digital platforms, which are believed to generate digital and relational resources that can facilitate and deliver innovations for firms. Instead of focusing on the extent of digital integration capability (DI), this paper seeks to empirically evaluate whether the DI asymmetry between the buyer and supplier firms influences bilateral information sharing and the buyer’s product innovation. We also examine the moderating effects of firms’ external (environmental dynamism) and internal (innovative climate) environments on these relationships.

Primary and secondary archival data on 180 buyer-supplier Chinese dyadic relationships were collected and analyzed using multiple linear regression models. Additionally, the Process macro was used to shed a nuanced light on the moderation effects of environmental dynamism and innovative climate.

The results show that DI asymmetry negatively impacts buyer firms’ product innovation through decreased information sharing. Environmental dynamism weakens the negative relationship between DI asymmetry and information sharing. Meanwhile, the innovative climate negatively moderates the relationship between information sharing and product innovation.

This study adds knowledge to the literature regarding the dark side of “one-sided digitalization.” By exploring the influences of unbalanced DI in buyer-supplier relationships, this study yields essential theoretical and managerial implications for product innovation success in a digital era.

This study explores how information volume affects crowdfunding success and identifies the signals – operational transparency, past crowdfunding experience, perceived project authenticity and perceived product quality – that moderate this relationship. The goal is to provide insights into managing information overload and enhancing the probability of funding success in various information volume contexts.

Data were collected from 2,681 Kickstarter campaigns and analyzed using fixed effects logit regression models.

The study reveals a curved relationship between information volume and funding success, moderated by factors such as operational transparency, crowdfunding experience, project authenticity and product quality.

This study provides fund-seekers with essential insights into disseminating information effectively.

This study contributes to the literature by elucidating the complex dynamics among information volume, signaling types and crowdfunding success, offering a nuanced understanding of how fund-seekers can optimize their campaigns for better outcomes.

This study conducts a systematic review to analyze the impact of blockchain technology and smart contracts on digital entrepreneurial finance and venture funding. It aims to investigate how these technologies can transform business operations, offering enhanced transparency, security and efficiency in various financial contexts.

A systematic literature review was conducted following PRISMA guidelines to assess the effectiveness of blockchain and smart contracts in generating business value. The study used the Scopus database to identify relevant articles published between 2015 and 2023. Quantitative and qualitative analyses were performed on the data using IRAMUTEQ software and Bibliometrix tool, both based in the “R” programming language.

The study reveals significant potential for blockchain and smart contracts to disrupt traditional venture funding models by automating contract execution and reducing administrative costs. Blockchain’s secure, decentralized ledger offers advantages in peer-to-peer transactions and risk mitigation, particularly in supply chain management and international trade. However, challenges related to scalability, energy consumption and regulatory compliance were also identified.

Despite the contributions, systematic review of the literature has limitations. Only articles in English, published in journals, were considered for this research, omitting, for example, conference articles and research in other languages, which may also contain relevant information.

The study contributes to the existing literature by synthesizing recent advancements in blockchain and smart contract applications within entrepreneurial finance. It highlights the transformative potential of these technologies while addressing their limitations and offering insights into future research directions. The findings provide valuable implications for academics, practitioners and policymakers interested in leveraging blockchain for financial innovation.

The purpose of this paper is the dynamic analysis and seismic damage assessment of steel sheet pile quay wall with inelastic behavior underground motions using several accelerograms.

Finite element analysis is conducted using the Plaxis 2D software to generate the numerical model of quay wall. The extension of berth 25 at the port of Bejaia, located in northeastern Algeria, represents a case study. Incremental dynamic analyses are carried out to examine variation of the main response parameters under seismic excitations with increasing Peak ground acceleration (PGA) levels. Two global damage indices based on the safety factor and bending moment are introduced to assess the relationship between PGA and the damage levels.

The results obtained indicate that the sheet pile quay wall can safely withstand seismic loads up to PGAs of 0.35 g and that above 0.45 g, care should be taken with the risk of reaching the ultimate moment capacity of the steel sheet pile. However, for PGAs greater than 0.5 g, it was clearly demonstrated that the excessive deformations with material are likely to occur in the soil layers and in the structural elements.

The main contribution of the present work is a new double seismic damage index for a steel sheet pile supported quay wharf. The numerical modeling is first validated in the static case. Then, the results obtained by performing several incremental dynamic analyses are exploited to evaluate the degradation of the soil safety factor and the seismic capacity of the pile sheet wall. Computed values of the proposed damage indices of the considered quay wharf are a practical helping tool for decision-making regarding the seismic safety of the structure.

Using the cognitive-affective-normative (CAN) model, this study highlights the role of self-regulated learning (SRL) and organisational culture and delves into the link between technophobia and a manager’s intention to adopt generative artificial intelligence (AI) in management practices.

An empirical study was conducted through a survey of 528 business managers from China.

The study reveals that technophobia is negatively related to a manager’s intention to adopt generative AI, while SRL is positively related to the intention to adopt generative AI. Moreover, SRL reduces the negative impact of technophobia on AI adoption. Open organisational cultures reduce the need for SRL.

This study goes beyond a purely technical perspective towards a “human-side” view on understanding managers’ adoption of generative AI. This study is an early attempt to apply the CAN model to analysing the connection between technophobia, SRL, organisational culture and the intention to adopt generative AI.

This study explores the formation process of cognitive destination image among first-time Chinese millennial tourists visiting Iran.

Employing a comprehensive mixed-method exploratory approach, blending qualitative and quantitative methodologies, we aim to construct a conceptual model explaining the complex process of tourists’ cognitive destination image development. In the qualitative phase, interviews with 15 Chinese millennials unveiled key factors such as perceived behavioral control, perceived product quality, on-site involvement, engagement, and prior destination image as fundamental influencers of tourists’ cognitive destination image. Subsequently, in the quantitative phase, involving a questionnaire survey with 229 first-time Chinese travelers, we proposed a conceptual model to validate our primary findings.

The results highlight the emergence of on-travel cognitive image as a developmental concept originating from tourists' on-site participation and pre-existing perceptions of the destination. Moreover, we identified perceived behavioral control as the primary antecedent of millennials’ image formation, directly affecting the destination’s image development. Furthermore, increased involvement and engagement were found to diminish perceived behavioral control. Additionally, perceived product quality prompted millennials to engage more with cultural attractions and activities, enriching their in-situ image.

The findings offer valuable insights for destination managers, enabling them to construct tailored strategies to augment the cognitive destination image.

This study provides a novel understanding of the cognitive destination image formation process among Chinese millennial tourists, highlighting the crucial role of perceived behavioral control, involvement, engagement, and perceived product quality. These insights can guide destination managers in enhancing the overall tourist experience and destination appeal.

This study investigates the sustainability models of non-profit and hybrid organizations, which aim to balance economic, social and environmental objectives. The research introduces the Sustainability Model Canvas to analyze these organizations and identify common patterns, unique characteristics and managerial insights to balance the triple bottom line.

The research utilizes the Sustainability Model Canvas to examine the sustainability models of 200 non-profit and hybrid organizations. Data were collected from secondary sources, including articles, reports and websites. The analysis was conducted using the activity system theoretical framework, which helped to identify design elements and themes within the business models of the studied organizations.

The study reveals four primary sustainability model patterns: donated income, earned income, public income and auto-generated income. An additional mixed approach pattern is identified, combining elements from the four primary patterns. The research highlights the parallels between these sustainability models and multi-sided platform business models, offering managerial suggestions for leveraging these patterns to achieve sustainability.

The study is based on secondary data, which may limit the depth of insights compared to primary data collection. At the same time, the chance to consider hybrid organization through multi-sided platform lenses provides relevant contributions to both the literature streams.

The identified sustainability model patterns and managerial suggestions can serve as blueprints for non-profit and hybrid organizations aiming to design or innovate their sustainability models. The Sustainability Model Canvas offers a practical tool for organizations to visualize and balance their triple bottom line objectives.

The research underscores the importance of integrating social and environmental considerations into business models, promoting a holistic approach to sustainability that can lead to broader social and environmental benefits.

This research contributes to the business model literature by extending the focus beyond traditional profit-oriented organizations to include non-profit and hybrid organizations. The introduction of the Sustainability Model Canvas provides a new tool for designing and analyzing sustainability-oriented business models. The study also suggests considering sustainability models as multi-sided platforms, offering new insights for both academic and practical applications.

This paper analyzes employees’ perceptions of data collection processes for human resource analytics (HRA). More specifically, we study the effect that information sharing practices have on employees’ attributions (i.e. benevolent vs malevolent) through the perceived legitimacy of data collection and monitoring processes. Moreover, we investigate whether employees’ emotional reaction (i.e. fear of datafication) depends on their perceived legitimacy and attributions.

The research is based on a sample of 259 employees operating for an Italian consulting firm that developed and implemented HRA processes in the last 3 years. The hypothesized model has been tested using structural equation modeling (SEM) on Stata 14.

This paper demonstrates the mediating role of perceived legitimacy in the relationship between information sharing practices and employees’ benevolent and malevolent attributions about data collection and monitoring processes for HRA practices. Results also reveal that perceived legitimacy predicts employees’ fear of datafication, with benevolent attributions that partially mediate this relationship.

This research indicates that employees perceive, try to make sense of and emotionally react to HRA processes. Moreover, we reveal the crucial role of information sharing practices and perceived legitimacy in determining employees’ attributions and emotional reactions to data collection and monitoring processes.

Combining human resource (HR) attributions, HR system strength, information processing and signaling theories, this work explores employees’ perception, attributive processes and emotional reactions to data collection processes for HRA practices.