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This study aims to examine the enablers of productivity of enterprise-level Agile development process using modified total interpretative structural modeling (TISM). The two main objectives of the current study are to determine the variables influencing enterprise-level agile development productivity and to develop modified TISM for the corresponding components.

To identify enablers of the productivity of enterprise-level agile software development process a literature review and opinions of domain experts were collected. A hierarchical relationship among variables that show direct and indirect influence is created using the modified TISM (M-TISM) technique with Cross Impact Matrix-Multiplication Applied to Classification analysis. This study examined and analyzed the relationships between the determinants within the enterprise using a M-TISM technique.

With the literature review, the study could identify ten enabling factors of the productivity of Agile development process at the enterprise level. Results depict that program increment (PI) planning and scalable backlog management, continuous integration and continuous delivery (CI/CD), agile release trains (ART), agile work culture, delivery excellence, lean and DevOps practices, value stream mapping (VMS), team skills and expertise, collaborative culture, agile coaching, customer engagement have an impact on the productivity of enterprise-level Agile development process. The results show that team collaboration, agile ways of working and customer engagement have a greater impact on productivity improvement for enterprise-level Agile development process.

The developed model is useful for organizations employing scaled Agile development processes in software development. This study provides a recommended listing of key enablers, that may enable productivity improvements in the Agile development process at the enterprise level. Strategists should focus on team collaboration and Agile project management. This study offers a modified TISM model to academicians to help them understand the effects of numerous variables on maintaining the productivity of an enterprise-level Agile. The identified characteristics and their hierarchical structure can help project managers during the execution of Agile projects at the enterprise level, more effectively, increasing their success and productivity.

The study addresses the gap in the literature by interpretative relationships between the identified enabling factors. The model validation is carried out by a panel of nine experts from several information technology organizations deploying Agile software development at the enterprise level. This unique method broadens the knowledge base in Agile software development at scale and provides project managers and practitioners with a practical foundation.

This paper aims to promote the higher quality development of high-tech enterprises in China. While science and technology have greatly promoted human civilization, resources have been excessively consumed and the environment has been sharply polluted. Therefore, it is particularly important for current enterprises to make use of scientific and technological innovation to maximize the benefits of mankind, minimize the loss of nature, and promote the sustainable development of our country.

By using DEA-Banker-Charnes-Cooper (BCC) model and DEA-Malmquist model, this paper comprehensively examines the innovation efficiency of high-tech enterprises from both static and dynamic perspectives, and conducts a provincial comparative study with the panel data of ten representative provinces from 2011 to 2020.

The research findings are as follows: the rapid number increase of high-tech enterprises in most provinces (cities) is accompanied by an ineffective input–output efficiency; the quality of high-tech enterprises needs to comprehensively examine both input–output efficiency and total factor productivity; and there is not a positive correlation between element investment and innovation performance.

Because the DEA model used in this paper assumes that the improvement direction of invalid units is to ensure that the input ratio of various production factors remains unchanged but sometimes the proportion of scientific and technological activities personnel and the total research and development investment is not constant. In the future, the nonradial DEA model can be considered for further research. Due to historical data statistics, more provinces, cities and longer panel data are difficult to obtain. The samples studied in this paper mainly refer to the provinces and cities that ranked first in the number of national high-tech enterprises in 2020. Limited by the number of samples, DEA analysis failed to select more input and output indicators. In the future, with the accumulation of statistical data, the existing efficiency analysis will be further optimized.

Aiming at the misunderstanding of emphasizing quantity and neglecting quality in the cultivation of high-tech enterprises, this paper comprehensively uses DEA-BCC model and DEA Malmquist index decomposition method to make a comprehensive comparative study on the development of high-tech enterprises in ten representative provinces (cities) from two aspects of static efficiency evaluation and dynamic efficiency evaluation.

The purpose of this study is to explore the mechanism of digitalized transformation in organizations’ human resource management (HRM). This study summarizes three basic factors driving the digital transformation process in China: level of perception, level of application and speed of transformation.

This study analyzes the strategic transformation process of HRM in Haier, Hisense and Chambroad to explore the human resource digital transformation mechanism in Chinese enterprises.

The results of this study show that three HR value chain models can be constructed based on how well HRM deals with business: the efficiency-oriented HRM value chain, quasi-business-oriented HRM value chain and business-oriented HRM value chain. The basic factors – level of perception, level of application and speed of transformation – are observed in the entire HRM digital transformation process.

This study provides theoretical and empirical insights for enterprises to explore the value of digital technology in HRM and facilitate the digital transformation of HRM.

Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.

This research studies the development of the evolving dynamic system model and explores the important elements or factors and what detailed attributes are the main influences model in achieving the success of a business, industry and management. It also identifies the real and major differences between static and dynamic business management models and the detailed factors that influence them. Later, this research investigates the benefits/advantages and limitations/disadvantages of some research studies. The studies conducted in this research put more emphasis on the capabilities of system dynamics (SD) in modeling and the ability to measure, analyse and capture problems in business, industry, manufacturing etc.

The research presented in this work is a qualitative research based on a literature review. Publicly available research publications and reports have been used to create a research foundation, identify the research gaps and develop new analyses from the comparative studies. As the literature review progressed, the scope of the literature search was further narrowed down to the development of SD models. Often, references to certain selected literature have been examined to find other relevant literature. To do so, a supporting tool (that connects related articles) provided by Google Scholar, Scopus, and particular journals has been used.

The dynamic business and management model is very different from the static business model in complexity, formality, flexibility, capturing, relationships, advantages, innovation model, new goals, updated information, perspective and problem-solving abilities. The initial approach of a static system was applied in the canvas business model, but further developments can be continued with a dynamic system approach.

Based on this study, which shows that businesses are developing more towards digitalisation, wanting the ability to keep up with the era that is moving so fast and the desire to increase profits, an instrument is needed that can help describe the difficulties of the needs and developments of the future world. This instrument, or tool of SD, is also expected to assist in drawing future models and in building a business with complex variables that can be predicted from the beginning.

This study will contribute to the SD study for many business incubator research studies. Many practical in business incubator management to have a benefit how to achieve the business performance management (BPM) in SD review.

The significant differences between static and dynamics to be used for business research and strategic performance management. This comparative study analyses some SD models from many authors worldwide. Their goals behind their strategic business models and encounter for their respective progress.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

The paper aims to explore the roles and impact of design in incubating and accelerating social enterprises. It aims to understand design’s influence on social enterprise ecosystems and in improving outcomes for social enterprises.

The study used an exploratory, qualitative approach, using case studies and interviews. The comparative case-study methodology was applied to evaluate the influence of design on the development of social enterprises in the UK and South Korea and identify critical issues in their utilisation of design. Empirical data included: in-depth case studies of design utilisation practices (UK = 6; South Korea = 15) and design applications (UK = 2; South Korea = 2) for the growth of social enterprise and its ecosystem; 27 social enterprise/design experts (UK = 17; South Korea = 10); and 22 social enterprises (UK = 12; South Korea = 10). Content and thematic analysis were used to synthesise the findings.

Findings demonstrate the differing influences of design on social enterprise, from improving products/services and business models to enhancing social enterprise ecosystem support and networks. Future directions are suggested for applying design for social enterprise growth, business stage development and systematising interactions between the social enterprise and design sectors.

The research is based on case studies from only two countries. Further, the adoption of working definitions of social enterprise in the countries may result in the research underestimating the heterogeneity of social enterprise.

The findings contribute to optimising efficient ecosystem development to improve social enterprise competitiveness and innovation.

This paper establishes a research foundation on design for social enterprise, offering theoretical and practical insights into its impact on growth.

Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.

This study aims to assess the alignment of South Korea’s government-certified social enterprises (GCSEs) with prevailing social enterprise (SE) models, notably the entrepreneurial nonprofit, social cooperative and social business models delineated in the “Emergence of Social Enterprises in Europe” (Defourny and Nyssens, 2012, 2017a, 2017b) and the “principle of interest” frameworks (Defourny et al., 2021). Thereby, it seeks to situate these enterprises within recognized frameworks and elucidate their hybrid identities.

Analyzing panel data from 2016 to 2020 for 259 GCSEs, this study uses tslearn for k-means clustering with dynamic time warping to assess their developmental trajectories and alignment with established SE models, which echoes the approach of Defourny et al. (2021). We probe the “fluid” identities of semi-public sector SEs, integrating Gordon’s (2013) notion that they tend to blend various SE traditions as opposed to existing in isolation.

Results indicate that GCSEs do align with prevalent SE frameworks. Furthermore, they represent a spectrum of SE models, suggesting the versatility of the public sector in fostering diverse types of SEs.

The concept of a semi-public sector SE model has been relatively uncharted, even though it holds significance for research on SE typologies and public sector entrepreneurship literature. This study bridges this gap by presenting empirical evidence of semi-public SEs and delineating the potential paths these enterprises might take as they amalgamate various SE traditions.

This study aims to explore the relationship between the degree of state-owned enterprises’ (SOEs) mixed reform and the environmental response of enterprises, against the background of actively promoting the reform of mixed ownership in China.

The study is conducted on a sample of A-share listed manufacturing companies in Shanghai and Shenzhen of China, investigated for the period 2015 to 2020. The baseline regression results are robust to a series of robustness and endogeneity tests. To deal with the issue of endogeneity, the technique of instrumental variable method has been applied.

The study confirms the U-shaped effect of the depth and restriction of mixed ownership on SOEs’ environmentally responsive behaviour in the manufacturing industry, especially for lower environmental regulation and higher level of risk-taking firms. The findings indicate that the government, shareholders and other stakeholders of enterprises should not simply consider that the mixed reform is directly promoting or reducing the environmental response behaviour of enterprises.

SOEs should improve their shareholding structures to undermine performance enhancement at the expense of the environment and increase environmentally beneficial behaviours. Regulators and governments should improve the institutional mechanism of environmental regulation and make efforts to promote corporate awareness of the environment.

Although the adoption and implementation of environmentally friendly policies are costly, improved environmental response and other social responsibilities are helpful to corporate long-term growth and reputation and obtain more capital market attention. Therefore, firms would benefit from improving their environmental response to protect nature, as well as to enjoy the economic and social benefits of a better environmental response.

To the best of the authors’ knowledge, there is a lack of studies focussing on the environmental behaviour of SOEs of mixed reform. As the mixed reform in China has come to a climax phase in recent several years, SOEs of mixed reform is an ideal environment for research. The study focusses on manufacturing firms as these firms are more susceptible to contribute to environmental pollution, exploitation of natural resources and labour concerns.