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Work‐zone delay is very costly to the movement of goods and people. It is increasingly problematic for logistics management if the travel time or delay information cannot be estimated in an accurate way. This paper describes a study to investigate the effects of work zones, enhance computer‐based capability to estimate the associated work‐zone delays, assess the interrelationship of significant factors that affect work‐zone delays and develop a user‐friendly tool to assist transportation operations and logistics planning. A computerized information system, called lane‐occupancy‐delay estimation system (LODES), is developed to assess work‐zone delays that may affect short‐ or long‐term logistic activities. The results from trials and their implications are discussed and, finally, areas of further research are proposed.

In the context of innovation-driven development strategy, open innovation has become an important way for enterprises to gain competitive advantages on the path of innovation and development. However, with the increasing competition, enterprises' open innovation is restricted by some constraints. How to promote open innovation in the restricted situations has become an existing research gap. Based on the perspective of digital transformation, this paper discusses how to promote the open innovation of enterprises under the restricted situations and find its breakthrough path, and analyzes the moderating effect of innovation persistence and political relevance.

Due to the complexity and confidentiality of military–civilian integration enterprises, they have become typical innovation-restricted enterprises. In this study, it selects a-share listed companies in the field of military–civilian integration in China in 2016–2020 as the research sample, and uses the two-way fixed-effect model to analyze the proposed variables. Finally, the robustness of the results in this paper is verified by a series of robustness tests and endogeneity tests.

The results show that digital transformation facilitates open innovation in military–civil integration enterprises, and that innovation persistence and political relevance positively moderate the relationship between the two. Further, digital transformation can promote open innovation in military–civil integration enterprises by easing the financing constraints and reducing information asymmetry. Innovation persistence has a more pronounced positive moderating effect among civilian-to-military and SMEs, and digital transformation of firms in the South has a negative effect on open innovation, but innovation persistence and political relevance dampen this negative effect.

Previous studies on the restrictions of open innovation or its dark side are mostly case studies and qualitative research. In contrast, the superiority and novelty of this study is in the form of a typical innovation-restricted enterprises “civil-military integration enterprise” as the research sample, based on the perspective of digital transformation, through empirical analysis method to explore how to better implementation of open innovation in the restricted situations. The findings of the study can not only enrich the application of digital transformation and open innovation theory, but also provide practical guidance for military–civil integration innovation in restricted situations.

In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.

To explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.

The investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.

This study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.

In the context of constructing an integrated national strategic system, collaborative innovation among enterprises is the current social focus. Therefore, in order to find the interest relationship between multiple game subjects, to explore the influencing factors of collaborative innovation of civil-military integration enterprises. This paper constructs a collaborative innovation mechanism for military–civilian integration involving four game subjects (military enterprises, private enterprises, local governments, and science and technology intermediaries). It aims to solve and reveal the evolutionary game relationship among the four parties.

To explore the mechanism of military–civilian collaborative innovation involving four players, this study employs game theory and constructs an evolutionary game model for collaborative innovation with the participation of military enterprises, civilian enterprises, local governments, and technology intermediaries. The model reveals the evolutionary game patterns among these four entities, analyzes the impact of various parameters on the evolutionary process of the game system, and numerical simulation is used to show these changes more specifically.

The research findings demonstrate that active government subsidies promote cooperation throughout the system. Moreover, increasing the input-output ratio of research and development (R&D), the rate of technological spillovers, and the R&D investment of civilian enterprises all facilitate the tendency toward cooperation within the system. However, when the government chooses to actively provide subsidies, increasing R&D investment in military enterprises may hinder the tendency toward cooperation. Furthermore, central transfer payments, government punishment from the central government, and an increase in the information conversion rate of technology intermediaries may suppress the rate of cooperation within the system.

Most of the previous studies on the collaborative innovation of military–civilian integration have been tripartite game models between military enterprises, private enterprises, and local governments. In contrast, this study adds science and technology intermediaries on this basis, reveals the evolution mechanism of collaborative innovation of civil-military integration enterprises from the perspective of four-party participation, and analyzes the factors influencing the cooperation of the whole system. The conclusion of this study not only enriches the collaborative innovation evolution mechanism of military–civilian integration enterprises from the perspective of multiple agents but also provides practical guidance for the innovation-driven development of military–civilian integration enterprises.

The study explores the relationship between entrepreneurial cognitive styles, entrepreneurial orientation (EO) and innovation performance (IP) of organizations in northern India. It also investigates how the cognitive styles of entrepreneurs impact their orientation and influence their innovative performance.

A quantitative research design validates the proposed hypotheses. A survey was conducted using simple random and snowball sampling to gain responses from 150 entrepreneurs based in northern India. The structural relationships in the study were examined using ANOVA (Analysis of Variance) which is a statistical method used to assess whether there are significant differences in means amongst groups by comparing the variance.

Data analysis revealed that entrepreneurial cognitive styles significantly and positively impact EO. The innovativeness and proactiveness dimensions of EO affect IP.

Previous researchers have worked independently on cognitive style and EO. The present paper combines the impact of cognitive style and EO on IP to identify the missing links between the three constructs, which need to be added to the existing literature. The authors' findings are valuable for entrepreneurs seeking to identify the key factors contributing to developing effective strategies at the firm level, thereby driving IP. Furthermore, the authors' insights would assist potential entrepreneurs in distinguishing between the different cognitive characteristics that differentiate entrepreneurs from non-entrepreneurs and how they strategically decide based on market situations to enhance IP.

This study aims to accurately calculate the magnetic field distribution, which is a prerequisite for pre-design and optimization of electromagnetic performance. Accurate calculation of magnetic field distribution is a prerequisite for pre-design and optimization.

This paper proposes an analytical model of permanent magnet machines with segmented Halbach array (SHA-PMMs) to predict the magnetic field distribution and electromagnetic performance. The field problem is divided into four subdomains, i.e. permanent magnet, air-gap, stator slot and slot opening. The Poisson’s equation or Laplace’s equation of magnetic vector potential for each subdomain is solved. The field’s solution is obtained by applying the boundary conditions. The electromagnetic performances, such as magnetic flux density, unbalanced magnetic force, cogging torque and electromagnetic torque, are analytically predicted. Then, the influence of design parameters on the torque is explored by using the analytical model.

The finite element analysis and prototype experiments verify the analytical model’s accuracy. Adjusting the design parameters, e.g. segments per pole and air-gap length, can effectively increase the electromagnetic torque and simultaneously reduce the torque ripple.

The main contribution of this paper is to develop an accurate magnetic field analytical model of the SHA-PMMs. It can precisely describe complex topology, e.g. arbitrary segmented Halbach array and semi-closed slots, etc., and can quickly predict the magnetic field distribution and electromagnetic performance simultaneously.

Discussion of China's one-child policy generally centres on its demographic effects. Bereavement among parents of singleton children and the role of social capital in the bereavement process have been under-explored. The purpose of this paper is to focus on mothers who lost their only children during the Sichuan earthquake in 2008. The paper aims to discuss the under-explored yet crucial issues of the one-child policy – the ways in which Chinese bereaved mothers handle the death of their singleton children – and the roles that social capital can play in their bereavement process.

The author conducted eight case studies on bereaved mothers through home visits, semi-structured interviews and participation in public activities during August 2010 and May 2011. In-depth interviews were used to collect information from these bereaved mothers in Sichuan, China.

The case studies reveal two major experiences of bereaved mother whose familial support varies substantially. One major experience is shared by those who had received emotional support from husband (who offered bonding social capital), and were able to get through the psychological pain. Another experience is shared by bereaved mothers who lost their familial relations. Weak social ties (i.e. an NGO which offered bridging social capital) remained the only source of support. Policies can target at the latter group of mothers by helping them to organise themselves into community-based groups and help to relieve their frustration and grief.

These research findings have implications for the development of NGOs, as well as complementary support for community-based bereavement counselling and community care in China.

The purpose of this paper is to put forward a demand chain management (DCM) framework underpinned by the alignment theory and applies it to investigate the fashion apparel (FA) industry in China under the impacts of the latest economic transition.

An exploratory multiple case study methodology involving five Chinese FA firms, each with a different business model and ownership type, was employed. Semi-structured interviews, onsite observations and review of company documents were conducted to collect information for analysis.

Using a conceptual DCM framework as a guide for analysis, the study finds that companies with a higher level of alignment with the external market situation and among the three internal DCM dimensions, namely, market management, supply chain management (SCM), and organization management, appear to perform better under the rapidly changing economic conditions in China.

This study contributes to knowledge by reviewing thoroughly the literature on SCM evolution and develops a DCM framework based on alignment theory that represents the state of the art in this area. By extending the administration-integration-production-development (A-I-P-D) logic set adopted in the alignment theory, this study has also equipped the proposed framework with an empirical tool to measure alignment.

By applying the framework to examine the Chinese apparel industry under the impacts of the latest economic transition, this study provides practitioners in the industry with a framework to help formulate strategies and a tool to measure alignment. The findings of the case study also offer insights to the industry to thrive in the rapidly changing businesses environment with dynamic uncertainties.

This study extends the application of the A-I-P-D logic set under the alignment theory to the SCM field. This endeavor successfully transforms the proposed DCM framework from a theoretical concept to a practical tool to help evaluate empirically the alignment and strategic fit of a firm and potential relationship with firm performance. As the Chinese FA market has increasingly evolved under the impact of the globalization, the findings of this study not only assist the local FA companies in coping with the dynamic uncertainties but also shed light on the future developments of the global FA industry. Besides, the alignment measurement tool embedded in the proposed DCM framework can help enhance the chances of business success during implementation.

The purpose of this paper is to show how the EStra-Many method works on optimization problems characterized by high-dimensionality of the objective space. Moreover, a comparison with a more classical approach (a constrained bi-objective problem solved by means of NSGA-II) is done.

The six reactances of a compensation network (CN) for a wireless power transfer system (WPTS) are synthesized by means of an automated optimal design. In particular, an evolutionary algorithm EStra-Many coupled with a sorting strategy has been applied to an optimization problem with four objective functions (OFs). To assess the obtained results, a classical genetic algorithm NSGA-II has been run on a bi-objective problem, constrained by two functions, and the solutions have been analyzed and compared with the ones obtained by EStra-Many.

The proposed EStra-Many method identified a solution (CN synthesis) that enhances the WPTS, considering all the four OFs. In particular, to assess the synthesized CN, the Bode diagram of the frequency response and a circuital simulation were evaluated a posteriori; they showed good performance of the CN, with smooth response and without unwanted oscillations when fed by a square wave signal with offset. The EStra-Many method has been able to find a good solution among all the feasible solutions, showing potentiality also for other fields of research, in fact, a solution nondominated with respect to the starting point has been identified. From the methodological viewpoint, the main finding is a new formulation of the many-objective optimization problem based on the concept of degree of conflict, which gives rise to an implementation free from hierarchical weights.

The new approach EStra-Many used in this paper showed to properly find an optimal solution, trading-off multiple objectives. The compensation network so synthesized by the proposed method showed good properties in terms of frequency response and robustness. The proposed method, able to deal effectively with four OFs, could be applied to solve problems with a higher number of OFs in a variety of applications because of its generality.

The purpose of this paper is to describe TraceALL which is a Semantic Web (SW), ontology‐based, service‐oriented framework which aims to provide the necessary infrastructure enabling food industry (particularly SMEs) to implement traceability applications using an innovative generic framework.

The framework builds upon the idea of the Semantic Web and provides an open and extensible underlying platform that allows different traceability interconnected applications to be designed and developed. More specifically, the framework provides a formal, ontology‐based, general‐purpose methodology to support knowledge representation and information modelling in traceability systems. Additionally, it suggests an open application framework based on widely used Semantic Web standards. Finally it provides a set of core services for storing, processing and retrieving traceability information in a scalable way. These components, taken together, facilitate the efficient development of next generation traceability applications.

Based on a case study which the authors executed as a proof of concept and studying the relevant literature it was found that TraceALL facilitates the development of next generation traceability applications because, from a food safety perspective, it enables all stakeholders in the food supply chain to have an information trail that follows the product's physical trail, but at the same time is cost effective, easy to manage and applicable within a globalised, networked, interoperable economic environment.

To the best of the authors' knowledge, this is the first food traceability system based completely on solid existing standards of the Semantic Web initiative. The authors consider that the inspiring analogy between resources such as those described in the Semantic Web initiative and the core traceability concept of a Traceable Resource Unit (TRU) is an extremely useful concept for developing cost‐effective traceability applications that possess many key requirements, which are described in the paper.