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This research aims to explore the research data ethics governance framework and collaborative network to optimize research data ethics governance practices, to balance the relationship between data development and utilization, open sharing, data security and to reduce the ethical risks that may arise from data sharing and utilization.

This study explores the framework and collaborative network of research data ethics policies by using the UK as an example. 78 policies from the UK government, university, research institution, funding agency, publisher, database, library and third-party organization are obtained. Adopting grounded theory (GT) and social network analysis (SNA), Nvivo12 is used to analyze these samples and summarize the research data ethics governance framework. Ucinet and Netdraw are used to reveal collaborative networks in policy.

Results indicate that the framework covers governance context, subject and measure. The content of governance context contains context description and data ethics issues analysis. Governance subject consists of defining subjects and facilitating their collaboration. Governance measure includes governance guidance and ethics governance initiatives in the data lifecycle. The collaborative network indicates that research institution plays a central role in ethics governance. The core of the governance content are ethics governance initiatives, governance guidance and governance context description.

This research provides new insights for policy analysis by combining GT and SNA methods. Research data ethics and its governance are conceptualized to complete data governance and research ethics theory.

A research data ethics governance framework and collaborative network are revealed, and actionable guidance for addressing essential aspects of research data ethics and multiple subjects to confer their functions in collaborative governance is provided.

This study analyzes policy text using qualitative and quantitative methods, ensuring fine-grained content profiling and improving policy research. A typical research data ethics governance framework is revealed. Various stakeholders' roles and priorities in collaborative governance are explored. These contribute to improving governance policies and governance levels in both theory and practice.

Implementing enterprise risk management (ERM) systems in construction firms of developing countries like India is critical for targeting strong risk management strategies that support their growth. It requires such firms to holistically understand the major barriers in terms of their definitions, relationships with one another and interdependencies. Thus, this study aims to identify, model and analyze the barriers to implementing ERM in construction firms using interpretive structural modeling (ISM).

This study used a Delphi process to identify barriers to the implementation of ERM in Indian construction firms, ISM to model them and Matrice d’Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) to analyze their interrelationships.

The study’s results revealed that individual-level factors are the most important among the barriers present at the lowest level in the hierarchical model, whereas organizational commitment with the highest dependence power is present at the highest level in the hierarchical model.

Since the usage of ERM in the construction industry is highly culture-dependent and may have regional nuances, the data on ERM usage might accurately reflect the Indian construction industry but may not apply to other regions.

This study can be used to develop effective strategies to improve the implementation of ERM in construction firms in developing countries like India.

ERM is crucial for managing risks in Indian construction firms due to the high degree of complexity and uncertainty associated with construction projects coming from changes due to technological advancement, regulatory changes, changes in consumer preferences, global competition and other socioeconomic and political factors.

The study’s results will help researchers and practitioners working in the construction industry of developing countries like India to identify the challenges in adopting ERM systems. It will guide construction firms to appropriately develop risk management strategies for managing the inevitable risks in their complex project environments. This will help improve their contribution to the country’s economic development.

The dynamic and evolving nature of the market calls for attention to digital platform firms' survival strategies, building agility for persistence in a continuously changing business environment. In India, the government’s adoption of the Digital Policy is one such change in the business environment for the firms that impact almost all sectors. Such policies cause a disruption wherein digital platform firms must be agile and create a strategic response that will endure any changes. The present study attempts to gain insight into the competitive strategies adopted by the digital platform firms of the consumer durables industry in India, which are implemented to facilitate their growth.

The entire study is conducted in two phases. Phase one includes identifying strategies sampled digital platform firms adopted in response to the digitalization policy, and the second phase evaluates the significance of the adopted plans to persist.

While clubbing the 42 strategic responses to a few aggregate dimensions, the study found four types of responses adopted by the digital platform firms in the consumer durable industry to persist in the market. Using a two-step system, the Generalized Method of Moments (GMM) approach, the study found that all four dimensions are statistically significant, positively impacting these firms' profitability.

The study contributes to the knowledge base of strategic responses to persist for the incumbent platform firms in a dynamic business environment.

The study answers the pertinent research question of how such strategic decisions may be informed in favor of profitability.

Given the prevalence of protecting geoheritage tourism sites, Ladakh has enormous potential. However, Ladakh’s potential and developments in its growth as a geotourism destination have received scant consideration. As such, this paper aims to explore Ladakh’s key drivers as a potential geotourism destination through cognitive dissonance and protection motivation theories.

This paper conducted in-depth interviews with 86 geoscientists and tourism professionals to assess Ladakh’s potential as a geotourism destination. This paper used a qualitative approach to congregate four constructs based on the image difference of the consensus map.

Because of the interviewees’ heterogeneity and uniqueness, meaningful constructs in the consensus were included for each figure and cloud words. This paper concluded that four drivers are the main forces behind geotourism development.

This paper explores the drivers – geotourism services, legislative requirements, experiential geotourism and SPARC (scientific, preservation, aesthetic, recreational, cultural) values – affecting geotourism in Ladakh. It is feasible to lessen the negative effects of overtourism and make sure that Ladakh’s distinctive nature is preserved for future generations by implementing sustainable tourism practices.

The world is on the verge of entering the deglobalization age, and industrialized economies have ushered it in. However, there is still a scarcity of comprehensive and rigorous studies in this field. This research has tried to analyze the evolution and characteristics of deglobalization research.

The authors have employed bibliometric analysis for examining the existing evidence on accelerating deglobalization thinking based on a thorough analysis of articles published during a roughly 25-year span between 1996 and 2022. This study has used the TISM-P technique to study the relationship among the factors accelerating deglobalization thinking. This research reviews the articles on several dimensions of deglobalization using the “what”, “why”, “how”, “who”, “when” and “where” approaches.

The authors specify the critical factors, policy reforms, approaches and observed characteristics explored in this developing research area.

The authors have analyzed the factors accountable for rising deglobalization thinking and also suggested strategic recommendations based on the findings to minimize the adverse impact of globalization.

Although there is a wealth of literature on globalization, very little study has been done in the field of deglobalization. This is the first substantive review being done in the deglobalization domain. The contemporary research has used the bibliometric approach and the “5W and 1 H” framework to gain a comprehensive understanding of the changing paradigm.

For survival and prosperity, enterprises must pursue exploitative and exploratory innovations simultaneously. To accelerate technological breakthroughs in the wind power industry, the Chinese Government has promulgated several support programs from the demand and supply sides. This study assesses the impact of different categories of innovation policies on exploitative and exploratory innovation. As women also play an increasingly important role in corporate governance, the authors also elucidate the moderating role of female executives in these relationships.

Based on micro-data of 119 listed Chinese wind power firms during 2006–2020, this study provides a theoretical model and tests the hypotheses.

Both demand-side and supply-side innovation policies significantly facilitate exploitative and exploratory innovations of in the Chinese wind power industry. Furthermore, female executives enhance the effects of these policies on exploitative innovation but negatively moderate their effects on exploratory innovation.

Innovation is generally considered homogeneous. This is one of the first studies to evaluate the impact of different categories of innovation policies on exploitative and exploratory innovations. In addition, although the increasingly important role of women in corporate governance is acknowledged, whether and how female executives affect the effectiveness of innovation policies has not been fully explored. This study advances the understanding of the potential impact of female executives on innovation policy effectiveness.

Wind power is the most promising renewable energy source in China. The development of digital technologies has brought about unprecedented growth opportunities and prospects for wind power. However, the relationship between digital technology adoption and total factor productivity (TFP) in the wind power industry in China has not been empirically assessed. This study aims to clarify whether and how digital technology adoption affects the TFP of the wind power industry in China.

Based on the data of listed companies in the Chinese wind power industry from 2006 to 2021, this study proposes and verifies relevant hypotheses with two-way fixed effects regression models.

The empirical results indicate that digital technology adoption is the cornerstone of the TFP of China’s wind power industry. Reconfiguration capability and technological innovation serially mediate the above relationship. In addition, the incentive effect of digital technology adoption varies among wind power firms. The impact of digital technology adoption is more significant in firms that are old and located in economically undeveloped regions.

This study is one of the earliest attempts to investigate the relationship between digital technology adoption and TFP in the renewable energy sectors of emerging economies. By integrating dynamic capability theory and the analytical framework of “Capability-Behavior-Performance” into the digital context, this study offers the theoretical insights into how digital technology adoption can enhance organizational reconfiguration capability, thereby stimulating technological innovation and subsequent TFP. Additionally, the impacts of different digital technologies are estimated in entirety, rather than in isolation.

The objective of the study is to investigate the factors that differentiate long-term shareholder value (LTSV) creating firms from LTSV destroying firms.

Through the review of literature, the hypothesis for the study is developed. To test the hypothesis, the study collects data from S&P BSE 500 companies listed in Bombay Stock Exchange (BSE). Based on the average overall return to shareholders for the period from year 1991 to 2019, the study identifies top 25 LTSV creating and LTSV destroying firms. The top 50 firms form the basis of this study. The study uses descriptive statistics and independent sample t-test to test the hypothesis of the study.

Among the variables investigated such as capital management policy and effective capital management practices, business and financial strategy, intellectual capital strategy, relational capital strategy and human capital strategy, the study found effective capital management and governance as a long-term source of value for shareholders.

The study highlights the importance of inclusion of value-relevant information in the annual report of the company. The study also supports the proposition that discretionary disclosure of intangible assets is relevant for the market to enable market participants to reasonably comprehend the fair value of the firm.

Adoption of a reporting framework that ensures the availability of all value-relevant information including off-balance-sheet resources is in the interest of the investors and policymakers alike.

This is a first such study exploring the value-relevant information and the source of long-term value for listed firms.

By exploring the microimplementation mechanism of common prosperity, this paper aims to offer a strategic direction for Chinese enterprises to achieve sustainable development. It also provides theoretical support and practical guidance for the Chinese Government in exploring feasible paths to common prosperity, starting from the enterprises.

This paper takes the digital business model innovation of Rainbow Planet as a case study, systematically explicating the mechanism through which digital business model innovation fosters common prosperity by constructing a research framework of “digital business model innovation-resource orchestration-common prosperity.”

First, from a microperspective, the role of enterprises in promoting common prosperity in China is confirmed. Second, based on the theory of resource orchestration, it is concluded that digital resources can generate three types of digital effects, such as association, interaction and feedback, through effective resource orchestration under the support of the value elements of the business model. Finally, this paper emphasizes that enterprises should take actions such as demand aggregation, trust building and relationship reshaping to connect with relevant stakeholders, so as to achieve the win-win purpose of improving enterprise competitiveness and deepening common prosperity.

For Chinese enterprises, linking their development with the overall welfare of society is an essential path to sustainable development. Enterprises can promote the integration of their development with social welfare in three aspects: enhancing the efficiency and innovation capability of digital operations, strengthening cooperation with stakeholders and advancing sustainable business models. For the Chinese Government, it is important to encourage enterprises to play a positive role in the fields of economy, environment and society. The government can promote excellent practices in digital innovation, social responsibility and environmental protection among enterprises by publicizing successful cases, inspiring more enterprises to follow suit.

Currently, engineering project design lacks a design framework that fully combines subjective experience and objective data. This study develops an aided design decision-making framework to automatically output the optimal design alternative for engineering projects in a more efficient and objective mode, which synthesizes the design experience.

A database of design components is first constructed to facilitate the retrieval of data and the design alternative screening algorithm is proposed to automatically select all feasible design alternatives. Then back propagation (BP) neural network algorithm is introduced to predict the cost of all feasible design alternatives. Based on the gray relational degree-particle swarm optimization (GRD-PSO) algorithm, the optimal design alternative can be selected considering multiple objectives.

The case study shows that the BP neural network-cost prediction algorithm can well predict the cost of design alternatives, and the framework can be widely used at the design stage of most engineering projects. Design components with low sensitivity to design objectives have been obtained, allowing for the consideration of disregarding their impacts on design objectives in such situations requiring rapid decisions. Meanwhile, design components with high sensitivity to design objective weights have also been obtained, drawing special attention to the effects of changes in the importance of design objectives on the selection of these components. Simultaneously, the framework can be flexibly adjusted to different design objectives and identify key design components, providing decision reference for designers.

The framework proposed in this paper contributes to the knowledge of design decision-making by emphasizing the importance of combining objective data and subjective experience, whose significance is ignored in the existing literature.