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Study on the internal legalization process of strategic change for a large number of ultra-large enterprises in China.

This paper takes formulation process of Suning Appliance Group’s 10-year strategy (2010–2020) as the research case, designs the research issues, propositions and analysis unit of the case study, and uses the data collection and analysis methods in the grounded theory to realize the theoretical development from data to viewpoint conceptualizing and to proposition categorizing.

There are four key concepts that affect the judgment of overall strategic legitimacy of super-large enterprises: Emerging-market opportunities and strategic operational positioning, legitimacy perspective mainly manifests as legitimacy judgment of strategic direction within organization. Positioning of core resources (including intangible resources) and their value identification methods or value evaluation criteria, the legitimacy perspective is mainly reflected in the organization's internal legitimacy judgment of functional planning, especially implementation path. The impact factors of the key performance of each SBU are positioned, and the legitimacy perspective is mainly reflected in the organization’s internal judgment on the legitimacy of strategic supporting measures, especially the resources needed for the implementation of the strategy and capacity development. The periodical strategic objectives and performance measurement indicators of each SBU are mainly reflected in the organization’s internal legitimacy judgment on strategic alignment and specific action plans for strategic operational units. The legitimacy of these four key concepts is strongly influenced by the rationality of these strategic concepts, which are closely related to their shaping patterns driven by right-brain and left-brain thinking modes.

This case is a longitudinal study of the strategic decision-making process, not a longitudinal follow-up of the actual implementation of the strategy. In addition, given that the case enterprise was facing the emerging market at that time and focused on pushing firms to seize opportunities, not much research has been done on the impact of external legitimacy on the strategic formulation process, a variable that is increasingly being focused on today.

This model has guidance significance and practical demonstration role for a large number of enterprises that are implementing the “+Internet” strategic change under traditional offline operation.

According to the summary of the connection between data and propositions in several rounds, this paper constructs a theoretical model of left and right brain thinking mode driving key concepts to achieve the internal legalization process of strategic changes.

In the analysis process, the legalization theory and the sense-making method are introduced into enterprises’ strategy making process. Based on this analysis framework, this paper analyzes in detail that the top decision-making level and the middle and high executive level form key strategic concepts to promote the internal legalization process of strategic decision-making driven by the right-brain intuitive thinking mode and the left-brain rational thinking mode, which greatly improves the quality of strategy formulation and the operability of strategy implementation.

The purpose of this paper is to develop a multistakeholder scale for assessing an excellent human resource (HR) function to demonstrate the extent to which it is focused on creating value from the perspective of its key internal and external stakeholders.

At the first stage, an in-depth literature review was conducted to extract the best practices for an excellent HR function. Then, to test the validation of the developed framework, it was sent to HR academics and practitioners in different countries. The survey responses were analyzed using the methods of the structural equation modeling (SEM) and confirmatory factorial analysis.

This study proposes an excellent HR multistakeholder assessment scale consisting of ten criteria based on the perceptions of internal and external HR stakeholders.

This study suggests a framework for assessing overall HR excellence based on the perceptions of key internal and external HR stakeholders. In addition, it is recommended that future researchers empirically test the developed scale across various industries and firm sizes.

HR managers, by using this framework, could continuously assess their HR excellence and compare their HR excellence with other companies’ HR excellence in the industry and then plan for continuous improvement in different HR areas to improve their stakeholders’ experiences.

This paper identifies the enablers and results of an excellent HR department and designs a multistakeholder feedback scale to better understand key internal and external HR stakeholders’ perceptions.

This paper aims to explore the epistemic connections between three instructional coaches and a first-year in-service teacher during remote planning and debrief meetings. Prior evidence suggests that remote instructional coaching leads to better teaching practices and identifies the instructional coaching moves used to prompt teacher reflection.

In this study, the authors utilized quantitative ethnography and epistemic network analysis (ENA) approaches to explore the epistemic frames of three remote university-based instructional coaches as they supported a first-year in-service teacher.

Quantitative ENA findings shed light on the network connections between instructional coaches and teachers, as well as the epistemic frames observed during planning and debrief meetings. Additionally, the authors provide qualitative findings that complement and reinforce the quantitative results.

All data collection occurred via Zoom, and the class was in a hybrid modality, with some students attending class in person and some attending remotely via Zoom. This unique context could have impacted the epistemic connections surrounding technology and logistics.

This study provides a practical codebook for use in future studies that explores instructional coaching. Findings from this study can be used to inform instructional coaching decisions.

The ENA findings helped deepen the authors' understanding of how instructional coaches can support a first-year in-service teacher during planning and debrief meetings in several ways. Additionally, this study presents a unique context given the COVID-19 pandemic and the remote model of instructional coaching.

Present study aimed to integrate Geographic Information Systems (GIS) and Building Information Modeling (BIM) in conjunction with multicriteria decision-making (MCDM) to enhance infrastructure investment planning.

This analysis combines GIS databases with BIM simulations for a novel highway project. Around 150 potential alternatives were simulated, narrowed to 25 more effective routes and 3 options underwent in-depth analysis using PROMETHEE method for decision-making, based on environmental, cost and safety criteria, allowing for comprehensive cross-perspective comparisons.

A comprehensive framework proposed was validated through a case study. Demonstrating its adaptability with customizable parameters. It aids decision-making, cost estimation, environmental impact analysis and outcome prediction. Considering these critical factors, this study holds the potential to advance new techniques for assessment and planning railways, power lines, gas and water.

The study acknowledges limitations in GIS data quality, particularly in underdeveloped areas or regions with limited technology access. It also overlooks other pertinent variables, like social, economic, political and cultural issues. Thus, conclusions from these simulations may not entirely represent reality or diverse potential scenarios.

The proposed method automates decision-making, reducing subjectivity, aids in selecting effective alternatives and considers environmental criteria to mitigate negative impacts. Additionally, it minimizes costs and risks while demonstrating adaptability for assessing diverse infrastructures.

By integrating GIS and BIM data to support a MCDM workflow, this study proposes to fill the existing research gap in decision-making prioritization and mitigate subjective biases.

The current difficulties of distribution network working robots are mainly in the performance and operation mode. On the one hand, high-altitude power operation tasks require high load-carrying capacity and dexterity of the robot; on the other hand, the fully autonomous mode is uncontrollable and the teleoperation mode has a high failure rate. Therefore, this study aims to design a distribution network operation robot named Sky-Worker to solve the above two problems.

The heterogeneous arms of Sky-Worker are driven by hydraulics and electric motors to solve the contradiction between high load-carrying capacity and high flexibility. A human–robot collaborative shared control architecture is built to realize real-time human intervention during autonomous operation, and control weights are dynamically assigned based on energy optimization.

Simulations and tests show that Sky-Worker has good dexterity while having a high load capacity. Based on Sky-Worker, multiuser tests and practical application experiments show that the designed shared-control mode effectively improves the success rate and efficiency of operations compared with other current operation modes.

The designed heterogeneous dual-arm distribution robot aims to better serve distribution line operation tasks.

For the first time, the integration of hydraulic and motor drives into a distribution network operation robot has achieved better overall performance. A human–robot cooperative shared control framework is proposed for remote live-line working robots, which provides better operation results than other current operation modes.

With production systems become more digitized, data-driven maintenance decisions can improve the performance of production systems. While manufacturers are introducing predictive maintenance and maintenance reporting to increase maintenance operation efficiency, operational data may also be used to improve maintenance management. Research on the value of data-driven decision support to foster increased internal integration of maintenance with related functions is less explored. This paper explores the potential for further development of solutions for cross-functional responsibilities that maintenance shares with production and logistics through data-driven approaches.

Fifteen maintenance experts were interviewed in semi-structured interviews. The interview questions were derived based on topics identified through a structured literature analysis of 126 papers.

The main findings show that data-driven decision-making can support maintenance, asset, production and material planning to coordinate and collaborate on cross-functional responsibilities. While solutions for maintenance planning and scheduling have been explored for various operational conditions, collaborative solutions for maintenance, production and logistics offer the potential for further development. Enablers for data-driven collaboration are the internal synchronization and central definition of goals, harmonization of information systems and information visualization for decision-making.

This paper outlines future research directions for data-driven decision-making in maintenance management as well as the practical requirements for implementation.

Assembly line is a common production form and has been effectively used in many industries, but the imprecise processing time of each process makes production line balancing and capacity forecasting the most troublesome problems for production managers. In this paper, uncertain man-hours are represented as interval grey numbers, and the optimization problem of production line balance in the case of interval grey man-hours is studied to better evaluate the production line capacity.

First, this paper constructs the basic model of assembly line balance optimization for the single-product scenario, and on this basis constructs an assembly line balance optimization model under the multi-product scenario with the objective function of maximizing the weighted greyscale production line balance rate, second, this paper designs a simulated annealing algorithm to solve problem. A neighborhood search strategy is proposed, based on assembly line balance optimization, an assembly line capacity evaluation method with interval grey man-hour characteristics is designed.

This paper provides a production line balance optimization scheme with uncertain processing time for multi-product scenarios and designs a capacity evaluation method to provide managers with scientific management strategies so that decision-makers can scientifically solve the problems that the company's design production line is quite different from the actual production situation.

There are few literary studies on combining interval grey number with assembly line balance optimization. Therefore, this paper makes an important contribution in this regard.

Academic institutions have the power to generate positive change by implementing sustainable development initiatives. This study aims to make a holistic assessment of the universities’ sustainability practices by explicitly focusing on equality and communication and by providing a general model for a university sustainability structure. In this context, the following questions were taken as references: How are the sustainability management mechanisms of universities? What are universities’ practices regarding “gender equality and equal opportunities”? How do universities integrate education, training, R&D and community development activities into their systems to be sustainable and how do they manage sustainability communication? This study aims to present an exemplary model for universities planning to develop a sustainability system and integrate the sustainable development goals (SDGs) into their ordinary work structures. It draws an exhaustive picture of what a sustainable structure and equality practices for universities look like by providing data about basic development areas regarding sustainability and social development.

This paper examines universities’ general sustainability system from a holistic standpoint to illustrate the implementation of sustainability practices within the universities’ plans and structure. In this qualitative research, the descriptive case study method is used. For this purpose, purposive sampling method is used where Jaume I University (Universitat Jaume I [UJI]) is selected as the sample due to its higher rankings despite its young age and its commitment to sustainability and equality. UJI is a public higher education and research university established in 1991 and is located in Castellón de la Plana in Valencia region of Spain. Its vision is to be a leading institution contributing to the social, cultural and economic aspects of sustainable development and to promote innovation, entrepreneurism, internationalization and social responsibility. It also has an non-governmental organization (NGO) working on equality. Three main data collection methods of descriptive research are used: (1) analysis of academic literature on sustainability in higher education institutions (HEIs); (2) document review: this review includes the systematic analysis of the case study university’s documents such as strategic plans, workflow charts, procedures and protocols of the related units. These documents were analyzed in a multidimensional way, and all related reports were examined comparatively. (3) Observation and semistructured interview notes: The interviews were conducted with nine unit managers and some academics working on this issue to obtain details surrounding the collected data. With this method, it became possible to obtain detailed data about the strategy and practices of the institution and identify the relationship between them. The research was conducted between April 2022 and September 2022.

According to the data, the main topics within the sustainability structure can be classified as (1) “sustainability in teaching system”, (2) “sustainability in research, development and innovation research, development and innovation (R&D&I) activities”, (3) “sustainability in management structure”, (3.1) governance, (3.2) ethics, (3.3) equality, (3.4) social responsibility and sustainability management and (3.5.) “networks and collaborations”, (4) “sustainability communication” and (5) “community development.” Each main heading includes subitems. In this context, 12 s subheadings and a total of 51 indicators under them have emerged. In addition to these, additional recommendations have been developed as a result of the analysis. This study’s findings reveal that sustainability is related to each unit of the university and that every unit engages in practices for sustainability. However, for holistic sustainability management, all practices should be coordinated and integrated according to a strategic goal. The current situation and strategic goals related to sustainability should also be defined in line with the university’s priority issues and stakeholders. Moreover, to achieve greater success and visibility, effective communication plays an important role. As such, alongside the conventional communication systems of academic units, it is crucial to establish a dedicated sustainability communication system as a distinct department.

This research is based on a case study method and is limited to the case of Jaume I University.

To the best of the authors’ knowledge, this research is an original study designed in line with the in-depth analysis of all systems of a university and also the data obtained through face-to-face interview methods.

The purpose of this paper is twofold: first, a case study on applying lean principles in manufacturing operations to redesign and optimize an electronic device assembly process and its impact on performance and second, introducing cardboard prototyping as a Kaizen tool offering a novel approach to testing and simulating improvement scenarios.

The study employs value stream mapping, root cause analysis, and brainstorming tools to identify root causes of poor performance, followed by deploying a Kaizen event to redesign and optimize an electronic device assembly process. Using physical models, bottlenecks and opportunities for improvement were identified by the Kaizen approach at the workstations and assembly lines, enabling the testing of various scenarios and ideas. Changes in lead times, throughput, work in process inventory and assembly performance were analyzed and documented.

Pre- and post-improvement measures are provided to demonstrate the impact of the Kaizen event on the performance of the assembly cell. The study reveals that implementing lean tools and techniques reduced costs and increased throughput by reducing assembly cycle times, manufacturing lead time, space utilization, labor overtime and work-in-process inventory requirements.

This paper adds a new dimension to applying the Kaizen methodology in manufacturing processes by introducing cardboard prototyping, which offers a novel way of testing and simulating different scenarios for improvement. The paper describes the process implementation in detail, including the techniques and data utilized to improve the process.

In recent years, railway systems worldwide have faced challenges such as the modernization of engineering projects, efficient management of intelligent digital railway equipment, rapid growth in passenger and freight transport demands, customized transport services and ubiquitous transport safety. The transformation toward intelligent digital transformation in railways has emerged as an effective response to the formidable challenges confronting the railway industry, thereby becoming an inevitable global trend in railway development.

This paper, therefore, conducts a comprehensive analysis of the current state of global railway intelligent digital transformation, focusing on the characteristics and applications of intelligent digital transformation technology. It summarizes and analyzes relevant technologies and applicable scenarios in the realm of railway intelligent digital transformation, theoretically elucidating the development process of global railway intelligent digital transformation and, in practice, providing guidance and empirical examples for railway intelligence and digital transformation.

Digital and intelligent technologies follow a wave-like pattern of continuous iterative evolution, progressing from the early stages, to a period of increasing attention and popularity, then to a phase of declining interest, followed by a resurgence and ultimately reaching a mature stage.

The results offer reference and guidance to fully leverage the opportunities presented by the latest wave of the digitalization revolution, accelerate the overall upgrade of the railway industry and promote global collaborative development in railway intelligent digital transformation.