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Although the literature recognizes that coopetition plays a significant role in the success of international construction joint ventures (ICJVs), the impacts of coopetition on the performance outcomes of ICJVs remain largely unknown. This study extends this line of research by theorizing coopetition from three dimensions, i.e. coopetition intensity, coopetition balance and coopetition structure, and examining the relationships between coopetition and ICJV performance outcomes from both the contingency and configuration perspectives.

The hypotheses were tested using survey data from a sample of 188 ICJVs. Structural equation modelling was employed for the contingency approach to estimate the relationships between the three dimensions of coopetition and performance. For the configuration approach, cluster analysis was utilized to identify coopetition patterns. Subsequently, an analysis of variance was employed to analyse the relationships between these coopetition patterns and performance.

The contingency results indicate that while coopetition intensity is positively related to all types of performance, coopetition balance is only positively related to project performance and partner performance. Moreover, coopetition structure is only related to partner performance and socioenvironmental performance. The configuration approach identifies six patterns of coopetition, manifesting different levels of project, partner and socioenvironmental performance.

These findings, therefore, contribute to the ICJV literature by extending the understanding of how coopetition dimensions individually and jointly influence ICJV performance.

The intricate dynamics of ChatGPT adoption among Indian students are discussed while exploring the factors outlined by Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). By assessing these factors, this study aims to unravel their impact on the behavioral intention to use ChatGPT.

While evaluating ChatGPT's adoption dynamics, this study analyses the UTAUT2 core factors and perceived benefits. Real-time data from 638 business and management students in India were collected through purposive sampling and a cross-sectional survey. An in-depth examination using IBM SPSS and AMOS revealed the patterns that regulate ChatGPT reception in educational settings.

Habit emerges as a powerful predictor, which aligns with the Habit Loop Theory's cues, routine and rewards. Perceived benefits significantly influence adoption, and traditional factors like performance expectancy and social influence exert no influence. The insignificance of effort expectancy challenges conventional understanding, unveiling novel aspects of student tech adoption.

There is a need for guidelines to ensure fair and responsible use of ChatGPT among students. While ChatGPT presents advantages like task automation and personalized learning, integrating it into the existing education system requires careful planning to harness its benefits effectively.

With the recent introduction of Generative-AI tools, understanding student acceptance and application is essential. This research sheds light on this emerging technology, emphasizing the importance of analyzing technology acceptance for its successful adoption.

The study aims to identify and understand the underlying behavioral tendencies and motivations influencing investor sentiments and examines the relationship between these underlying factors and investment decisions during the COVID-19-induced financial risks.

The study uses the primary data and information collected from 300 Indian retail equity investors using a nonprobability sampling technique, specifically purposive and snowball sampling. This research uses the insights from Phuoc Luong and Thi Thu Ha (2011) and Shefrin (2002) to delineate behavioral factors influencing investment decisions. Structural equation modeling estimates the causal relationship between underlying behavioral factors and investment decisions during the COVID-19-induced financial risks.

The study establishes that the “Regret Aversion,” “Gambler’s Fallacy” and “Greed” significantly influence investment decisions, and provide a comprehensive understanding of how psychological motivations shape investor behavior. Notably, “Mental Accounting” and “Conservatism” exhibit insignificance, possibly influenced by the unique socioeconomic context of the pandemic. The research contributes to 35% of variance understanding and prompts the researchers and policymakers to tailor investment strategies aligned to these behavioral tendencies.

The findings hold policy implications for investors and policymakers and provide tailored recommendations including investor education programs and regulatory measures to ensure a resilient and informed investment community in the context of India's evolving financial landscapes.

Theoretically, behavior tendencies and motivations have been strongly linked to investment decisions in the stock market. Yet, empirical evidence on this relationship is limited in developing countries where investors focus on risk management. To the best of the authors’ knowledge, this study is among the first to document the influence of underlying behavioral tendencies and motivation factors on investment decisions regarding retail equity in a developing country.

Several farm safety net strategies are available to farmers as a source of financial protection against losses due to price instability, government policies, weather fluctuations and global market changes. Producers can employ these strategies combining crop insurance policies with countercyclical policies for several crops and production areas; however, less is known about the efficiency of these strategies in enhancing profit and reducing its variability. In this study, we examine the efficiency of these strategies at minimizing inter crop year farm profit variability.

We utilized relative mean of profit and coefficient of variation, to compare counterfactually calculated farm safety net strategies for a sample of 28,615 observations across 2,486 farms and four dryland crops (corn, soybean, sorghum and wheat) in Kansas spanning nine crop years (2014–2022). A no farm safety net strategy is used as the benchmark for every alternative strategy to ascertain whether a policy customization is statistically different from a no farm safety case.

The general pattern of the results suggests that program combination strategies that have a high-profit enhancement potential necessarily have low profit risk for dryland wheat and sorghum production. On the contrary, such a connection is absent for dryland corn and soybeans production. Low-cost farm safety net strategies that enhance corn and soybeans profits do not necessarily lower profit risks.

This paper is one of the first to use a large sample of actual farm-level observations to evaluate how combinations of safety net programs offered under the Title I (PLC, ARCCO and ARCIC) and XI (FCIP) of the U.S. Farm Bill rank in terms of profit level enhancement and profit risk reduction.

Building upon the cognition-affect-behavior (CAB) model and script theory, this research aims to enrich the existing literature on historic town tourism consumption by offering empirical evidence of how the cognitive and affective images of historic towns contributes to tourists' memorable tourism experiences (MTE) and revisit intention, while identifying the cognitive image dimensions that are relevant for evaluating historic towns.

An on-site survey was conducted with 486 local tourists who visited the historic towns in Chengdu. partial least squares-structural equation modeling (PLS-SEM) was utilized to assess both the measurement and structural models.

(1) Cognitive image emerged as a significant predictor of affective image; (2) Both cognitive image and affective image had a positive influence on MTE, in which cognitive image played a more dominant role in shaping MTE; (3) MTE was found to strongly predict revisit intention among tourists; (4) MTE and affective image mediated the relationship between cognitive image and revisit intention.

This research highlights the value of incorporating cognitive and affective constructs in predicting MTE, and the proposed integrated framework of the CAB model and script theory exhibits superior predictive power in understanding tourists' revisit intention.

This research provides empirical insights about how historic towns improve their marketing strategies as short day-trip destinations.

This research provides a novel insight on the applicability of an integrated model combining the CAB model and script theory in explaining the revisit behavior of local tourists within the context of historic towns.

This aims to explore the relationship between the agile methods barriers in large-scale contexts and the benefits for business, team and product and process, exploring the organizational readiness (OR) mediating role.

We propose a theoretical model through survey-based research, applying partial least square structural equation modelling.

We confirmed that OR mediating effect on the relationship between agile methods barriers and team benefits. We operationalized OR in a broader context that embeds the strategic alignment of large-scale agile implementation, considering variables such as organizational structure and culture.

The data are cross-sectional rather than longitudinal, which limits temporal interpretations of the associations between agile methods and organizational issues.

The findings offer a way forward for organizations already using or planning to implement agile management to understand the pathway towards achieving the expected benefits. Our study also unveils the importance of looking at OR when implementing such a complex change in management from traditional to large-scale contexts.

Our results show the significant and positive influence of agile method on all three benefit variables (team, business, product and processes). Furthermore, we identified the significant and positive mediating role of OR on the relationship between agile method and team benefits.

This paper analyzes the value creation process in terms of the relationships between institutions, technology, integration of resources and contextual value. The study was conducted within an online learning setting in higher education, and utilized service-dominant logic as a basis for analysis.

A total of 349 responses were collected through an online survey. After removing data from respondents who did not meet the criteria and outliers, 280 responses were analyzed. Furthermore, six hypotheses were tested using structural equation modeling (SEM) techniques.

The results confirm that institutions are proven to influence technology and resource integration. The technology significantly affects resource integration and value-in-context. Likewise, resource integration determines value-in-context remarkably. On the other hand, this study found no evidence of the impact of institutions on value-in-context.

The study has been conducted in the Jabodetabek area, with a sample size of only 280. An extensive survey, including a larger sample size, may reveal a broader glimpse of the value co-creation process of students in higher education institutions. Only three antecedents of contextual value have been explored, namely institutions, technology and resource integration. More strengthening and detailed findings could be derived if the antecedents of the contextual value addressed could be added. In the sampling, the researchers have used non-probability sampling for collecting data due to various constraints. The use of the probabilistic sampling method might have given some new insights to the study and made the sample more representative. The convenient sampling method employed in this study may limit the generalization of this study's findings. Therefore, the findings of the hypothesis test only apply to the selected sample data. Another limitation of the study is that the survey respondents represented an urban Indonesian perspective. So, replication of this study in different areas (e.g. west, east and central Indonesia) would help to generalize the findings. In this study, there is no evidence that institutions have a direct impact on contextual value. The authors suggest reexamining the relationship between institutions and contextual value in future studies.

In particular, the authors have succeeded in designing a new empirical model in higher education based on the perspective of service-dominant logic (S-D logic). This finding further strengthens the existence of the perspective of S-D logic as a new general theory of the market.

Industry 4.0 has put forward a smart perspective on managing supply chain networks and their operations. The current manufacturing system is primarily data-driven. Industries are deploying new emerging technologies in their operations to build a competitive edge in the business environment; however, the true potential of smart manufacturing has not yet been fully unveiled. This research aims to extensively analyse emerging technologies and their interconnection with smart manufacturing in developing smarter supply chains.

This research endeavours to establish a conceptual framework for a smart supply chain. A real case study on a smart factory is conducted to demonstrate the validity of this framework for building smarter supply chains. A comparative analysis is carried out between conventional and smart supply chains to ascertain the advantages of smart supply chains. In addition, a thorough investigation of the several factors needed to transition from smart to smarter supply chains is undertaken.

The integration of smart technology exemplifies the ability to improve the efficiency of supply chain operations. Research findings indicate that transitioning to a smart factory radically enhances productivity, quality assurance, data privacy and labour efficiency. The outcomes of this research will help academic and industrial sectors critically comprehend technological breakthroughs and their applications in smart supply chains.

This study highlights the implications of incorporating smart technologies into supply chain operations, specifically in smart purchasing, smart factory operations, smart warehousing and smart customer performance. A paradigm transition from conventional, smart to smarter supply chains offers a comprehensive perspective on the evolving dynamics in automation, optimisation and manufacturing technology domains, ultimately leading to the emergence of Industry 5.0.

Flexibility and efficiency are dual attributes of the organizational structure that are crucial for project-driven enterprises to achieve sustainable development in a dynamic environment. However, there is a lack of research on the patterns by which the dual attributes of a project-driven enterprise’s organizational structure affect business model innovation. Employing organizational theory, this study aims to assess the mediating mechanisms and dynamic capabilities through which the dual attributes of the organizational structure influence business model innovation in project-driven enterprises.

Data were collected from 242 employees from four project-driven companies across 26 cities (e.g. Beijing, Tianjin, Guangzhou and Shenzhen) in China. Structural equation modeling revealed the relationship between organizational structure’s dual attributes and business model innovation.

The findings show that the dual attributes (flexibility and efficiency) of the organizational structure have positive impacts on business model innovation. Moreover, dynamic capabilities mediate the relationship between the dual attributes and business model innovation in project-driven enterprises.

This study provides contributions to innovation research in the context of project-driven enterprises by revealing the influence of organizational structure on business model innovation through the firms’ dynamic capabilities. Such knowledge can enable managers of project-driven enterprises to develop effective interventions to promote business model innovation.

The purpose of this study focused on a global longitudinal bibliometric mapping of research in the field of health biotechnology between 1990 and 2023 to determine who is leading this field of knowledge and to estimate the sub-disciplines that are emerging and project those that will prevail in the future.

The study identified the most relevant countries, institutions and researchers, as well as the type of scientific collaborations. The applied steps applied in the study were the following: identification and selection of keyword terms by a panel of experts; design and application of an algorithm to identify these selected keywords in titles, abstracts and keywords using Web of Science terms to contrast them; performance of JCR data processing during 2023 using R, Python and VOSviewer.

Among the most relevant conclusions of the study are the following exponential growth has been observed in the study period; new branches of knowledge have emerged in which the subjects have been acquiring their own autonomous capabilities; and R&D in this field is still concentrated in a small group of core countries, and the trend is for it to remain so due to the capacity needs required.

This contribution seeks to systematize the existing scientific knowledge in the field of biotechnology, specifically in the area of health, using the technique of scientific mapping based on a logical model of indicators that aims to determine potential thematic ramifications.