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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.

This paper aims to investigate the process by which performative technologies (PTs), in this case accreditation work in a business school, take form and how humans engage in making up such practices. It studies how academics come to accept and even identify with the quantitative representations of themselves in a translation process.

The research involved a longitudinal, self-ethnographic case study that followed the accreditation process of one Nordic business school from 2015 to 2021.

The findings show how the PT pushed for different engagements in various phases of the translation process. Early in the translation process, the PT promoted engagement because of self-realization and the ability for academics to proactively influence the prospective competitive milieu. However, as academic qualities became fabricated into numbers, the PT was able to request compliance, but also to induce self-reflection and self-discipline by forcing academics to compare themselves to set qualities and measures.

The paper advances the field by linking five phases of the translation process, problematization, fabrication, materialization, commensuration and stabilization, to a discussion of why academics come to accept and identify with the quantitative representations of themselves. The results highlight that the materialization phase appears to be the critical point at which calculative practices become persuasive and start influencing academics’ thoughts and actions.

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.

An experimental investigation for developing structure-property correlations of hot-rolled E410 steels with different carbon contents, i.e. 0.04wt.%C and 0.17wt.%C metal active gas (MAG) and cold metal transfer (CMT)-MAG weldments was undertaken.

Mechanical properties and microstructure of MAG and CMT-MAG weldments of two E410 steels with varying content of carbon were compared using standardized mechanical testing procedures, and conventional microscopy.

0.04wt.%C steel had strained ferritic and cementite sub-structures in blocky shape and large dislocation density, while 0.17wt.%C steel consisted of pearlite and polygonal ductile ferrite. This effected yield strength (YS), and microhardness being larger in 0.04wt.%C steel, %elongation being larger in 0.17wt.%C steel. Weldments of both E410 steels obtained with CMT-MAG performed better than MAG in terms of YS, ultimate tensile strength (UTS), %elongation, and toughness. It was due to low heat input of CMT-MAG that resulted in refinement of weld metal, and subzones of heat affected zone (HAZ).

A substantial improvement in YS (∼9%), %elongation (∼38%), and room temperature impact toughness (∼29%) of 0.04wt.%C E410 steel is achieved with CMT-MAG over MAG welding. Almost ∼10, ∼12.5, and ∼16% increment in YS, %elongation, and toughness of 0.17wt.%C E410 steel is observed with CMT-MAG. Relatively low heat input of CMT-MAG leads to development of fine Widmanstätten and acicular ferrite in weld metal and microstructural refinement in HAZ subzones with nearly similar characteristics of base metal.

The organizational digital transformation (ODT) in companies presents small and medium-sized enterprises (SMEs) – who remain at the beginning of this transformation – with the challenge of offering digital services based on sensor technologies. Against this backdrop, the present paper identifies ways SMEs can enable digital servitization through sensor technology and defines the possible scope of the organizational transformation process.

Around 21 semi-structured interviews were conducted with experts from different hierarchical levels across the German manufacturing SME ecosystem. Using the Gioia methodology, fields of action were identified by focusing on influencing factors and opportunities for developing these digital services to offer them successfully in the future.

The complexity of existing sensor offerings must be mastered, and employees' (data) understanding of the technology has increased. Knowledge gaps, which mainly relate to technical and organizational capabilities, must be overcome. The potential of sensor technology was considered on an individual, technical and organizational level. To enable the successful implementation of service offerings based on sensor technology, all relevant stakeholders in the ecosystem must network to facilitate shared value creation. This requires standardized technical and procedural adaptations and is an essential prerequisite for data mining.

Based on this study, current problem areas were analyzed, and potentials that create opportunities for offering digital sensor services to manufacturing SMEs were identified. The identified influencing factors form a conceptual framework that supports SMEs' future development of such services in a structured manner.

The purpose of this paper is to develop a coupled lattice Boltzmann model for the simulation of the freezing process in unsaturated porous media.

In the developed model, the porous structure with complexity and disorder was generated by using a stochastic growth method, and then the Shan-Chen multiphase model and enthalpy-based phase change model were coupled by introducing a freezing interface force to describe the variation of phase interface. The pore size of porous media in freezing process was considered as an influential factor to phase transition temperature, and the variation of the interfacial force formed with phase change on the interface was described.

The larger porosity (0.2 and 0.8) will enlarge the unfrozen area from 42 mm to 70 mm, and the rest space of porous medium was occupied by the solid particles. The larger specific surface area (0.168 and 0.315) has a more fluctuated volume fraction distribution.

The concept of interfacial force was first introduced in the solid–liquid phase transition to describe the freezing process of frozen soil, enabling the formulation of a distribution equation based on enthalpy to depict the changes in the water film. The increased interfacial force serves to diminish ice formation and effectively absorb air during the freezing process. A greater surface area enhances the ability to counteract liquid migration.

The circular economy (CE) promotes the recovery of value from waste while also working towards achieving long-term environmentally sustainable goals. The goal of this research is to explore the challenges, opportunities, future scope and green practices that small and medium-sized firms (SMEs) face as they move from the linear economy to the CE.

Based on a structured questionnaire, a survey was conducted with representatives from 163 SMEs in India. The data were analysed using co-variance based structural equation modelling technique.

This research identifies various challenges, including consumer acceptability, worries about awareness, recyclability issues, financial constraints and the absence of a defined management plan for SMEs in adopting the CE. Further, strong management will, innovation, technical up-gradation, training of employees, employee motivation and appropriate guidelines are recognized as essential possibilities for CE implementation.

While there has been some work on CE, no studies have directly compared these efforts with the goal of shifting from a linear economy to a CE. Given the transient nature of many archives, it is critical that the efforts put into them and the opinions of those who work in them be recorded so that communities can benefit from a shared linear economy in making decisions about their own history.

The purpose of this study is to establish the relationship between digital leadership and academic performance. It models the digitalization process, outlining why and how digital leadership is important for better academic performance. At the same time, this study examines the role of digital culture as a moderating variable in the direct relationship between main variables of the study. The study aims to expand the domain of academic performance at the university by including a much recent leadership-related aspect and organizational context of the digital culture.

The study opted for a descriptive study, using the survey instruments to collect the data. The sample population consisted of students currently enrolled at the Faculty of Business and Management, Universiti Teknologi MARA, Melaka, Malaysia. Based on the convenience sampling, 383 samples were drawn from the sample population. All items were adopted from previous literature, and expert feedback was obtained to examine the validity of the instruments. The data were analysed using SPSS and SmartPLS version 3.0.

This study provides empirical insights about how digital leadership is important for academic performance for the new millennials. Also, digital culture is found to provide significant moderation effect into the relationship. It suggests that universities must promote digitalization culture and embed the use of technology and digitalization into teaching and learning to cultivate a more effective learning process among university students. This is important as elements of digital leadership, including adaptive role, attitude, digital competency, digital skill and inspirational role, are found to significantly contribute to academic performance.

This study only focuses on samples taken from one of the faculties in one campus, thus limiting its scope. Future research is encouraged to replicate the same study setting to include larger sample size from different faculties, or perhaps from different universities. These propositions could help to better generalize the research findings on the practice of digital leadership on academic performance in the country. However, this study established a digital leadership model that can be applied to undergraduate students at the universities. Also, the inclusion of digital culture can strengthen the learning process.

This study includes implications for the development of digital leadership attributes and promoting digital culture within the university students and environment for engaging in a better academic performance. Digital leadership is found to be an important criterion of academic performance in this digital age society, and cultivating digital culture enhances students’ academic performance. These findings shall prompt the university to actively engage in fostering digitalization culture within the university. Also, the top management of the university should inform the students to be adaptive and cultivate the attributes of digital leaders, as their readiness to cope with the technological change has significant positive impact on their academic performance.

It is important to ensure that the future graduates that are being produced are ready to take on more challenges as digital leaders in the digital society. This might accelerate the country’s initiatives and efforts towards becoming a developed nation. Thus, investing in oneself to become digitally literate and competent might not only influence their academic performance, but they will also be equipped to fulfil one of the expectations of future employers of potential graduates, which is possessing digital leadership.

Digitalization is not only about the technology. It is about the people too. As the study on digital leadership is still in its infant stage, this study is unique as it is among the earliest to establish digital leadership constructs within the context of Malaysia. It informs the university that digital leadership provides significant contribution to academic performance. Thus, the university is encouraged to nurture digitalization, not only in the teaching and learning but also with the people within the university environment. Determining the right programs and plans for the curricular will help students to develop digital leadership attributes more effectively. Finally, improving digitalization among its students and culture is important, as these elements provide significant effect towards academic performance.

Road traffic emissions are generally believed to contribute immensely to air pollution, but the effect of road traffic data sets on air quality (AQ) predictions has not been fully investigated. This paper aims to investigate the effects traffic data set have on the performance of machine learning (ML) predictive models in AQ prediction.

To achieve this, the authors have set up an experiment with the control data set having only the AQ data set and meteorological (Met) data set, while the experimental data set is made up of the AQ data set, Met data set and traffic data set. Several ML models (such as extra trees regressor, eXtreme gradient boosting regressor, random forest regressor, K-neighbors regressor and two others) were trained, tested and compared on these individual combinations of data sets to predict the volume of PM_2.5, PM₁₀, NO₂ and O₃ in the atmosphere at various times of the day.

The result obtained showed that various ML algorithms react differently to the traffic data set despite generally contributing to the performance improvement of all the ML algorithms considered in this study by at least 20% and an error reduction of at least 18.97%.

This research is limited in terms of the study area, and the result cannot be generalized outside of the UK as some of the inherent conditions may not be similar elsewhere. Additionally, only the ML algorithms commonly used in literature are considered in this research, therefore, leaving out a few other ML algorithms.

This study reinforces the belief that the traffic data set has a significant effect on improving the performance of air pollution ML prediction models. Hence, there is an indication that ML algorithms behave differently when trained with a form of traffic data set in the development of an AQ prediction model. This implies that developers and researchers in AQ prediction need to identify the ML algorithms that behave in their best interest before implementation.

The result of this study will enable researchers to focus more on algorithms of benefit when using traffic data sets in AQ prediction.

This paper uses the complex proportionality assessment (COPRAS) method to examine the driving factors of Industry 4.0 (I4) technologies for lean implementation in small and medium-sized enterprises (SMEs).

Adopting I4 technology is imperative for SMEs seeking to maintain competitiveness within the manufacturing sector. A thorough understanding of the driving factors involved is required to support the implementation of I4. For this objective, the multi-criteria decision-making (MCDM) tool COPRAS was used to efficiently analyze and rank these driving elements based on their importance. These factors can help small and medium-sized firms (SMEs) prioritize their efforts and investments in I4 technologies for lean implementation.

This study evaluates and prioritizes the nine I4 factors according to the perceptions of SMEs. The ranking offers significant insights into the factors SMEs consider more accessible and effective when adopting I4 technologies.

The author's original contribution is to examine I4 driving factors for lean implementation in SMEs using COPRAS.