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In the pursuit of competitive advantage, an increasing number of firms are adopting open innovation (OI) strategies. However, previous studies have often overlooked the role of strategic human resource management (SHRM) in promoting OI. This study aims to fill this gap by examining how SHRM impacts OI through the mediating factors of intellectual capital (IC) and supply chain integration (SCI). This research sheds light on the critical interplay between SHRM, IC and SCI in driving OI success. The findings underscore the importance of adopting a comprehensive and integrated approach to OI that encompasses both resources and dynamic capabilities.

By integrating resource-based view with the dynamic capability perspective, the hypotheses were tested with a survey sample of 136 Chinese manufacture firms using hierarchical regression and bootstrap method.

The results show that SHRM has a positive effect on OI, and both IC and SCI are partial mediators of the relationship between SHRM and OI. In addition, the chain mediation effect of “SHRM-IC-SCI-OI” has further been verified.

This study uncovers the “black box” between SHRM and OI, and responds to the call for strengthening research on the relationship between SHRM and OI. The study indicates that firms should implement HR practices, including extensive training, team reward and internal promotion to promote the implementation of OI strategy.

In large enterprises, the notion is that an organization’s business strategy is a significant determinant of its human resource (HR) practices. However, there is limited evidence in the literature of such linkages for small and medium enterprises (SMEs). The purpose of this paper is to examine the nature and extent of the relationship between the types of business strategies used and HR practices, namely, staffing, training and employee relations among SMEs.

The authors have collected data from 168 SMEs manufacturing autoparts and purposively chosen three SME case studies to derive in-depth observations of business strategies and HR practices. Quantitative results from the survey indicate that these SMEs exhibit a logical relationship between the strategic posture of the SMEs and their adopted HR practices.

This study illustrates that SMEs operating in the risky and lesser developed labor markets of a lower-income country such as Pakistan adopt certain practices that differ considerably from firms operating in more competitive automotive markets using highly skilled labor. The findings suggest that there is a significant potential to be realized through strategically managing HR practices to achieve sustainable competitive advantage.

Education of supervisors and management and suitable skill level of labor in tandem with continuous cutting edge industrial training appear to be the most successful business strategy followed by Prospector and Analyzer SMEs. For greater efficiency they need to have dedicated HR management, and financial and auditing services. Meanwhile, public sector entities as well as representative business bodies need to provide targeted practical technical and financial training and assistance to strengthen Defender and Reactor SMEs and improve their range of outputs.

This study contributed to the SMEs’ management literature in the context of Pakistan because there are very few studies that have examined the impact of business strategy on the HR practices in SMEs manufacturing autoparts in the automotive industry of Pakistan. The case study approach captures detailed insights and identifies the areas where the SMEs in developing countries perform differently than the SMEs in developed countries.

This paper aims to explore the impact of flexible human resource management system (FHRMS) on employee innovation performance in Chinese context. The boundary conditions of employability and organizational identity are also discussed.

This study is based on 322 questionnaire survey from employees in China. The questionnaires were collected at two time points. This study used the method of multi-level linear model analysis for empirical test.

This study has three conclusions. First, FHRMS have a significant positive impact on employee innovation performance, with employability playing a mediating role. Second, organizational identity plays a moderating role between employability and employee innovation performance. Third, organizational identity moderates the mediating effect of a human source management systems on employee innovation performance through employability.

The results are helpful to open the “black box” of the influence of FHRMS on employees’ individual innovation performance. This study provides a reference for enterprises to establish flexible human source management system to improve employee innovation performance.

The construction industry activities play a key role in achieving socio-economic development and sustaining economic growth in many countries. Increased awareness about the role of human resource management in employee performance has led construction firms to evaluate and focus on high-performance work practices (HPWPs) components, which intend to cultivate employee and organizational performance. This study aims to explain HPWPs affect employee performances through the mediating influence of trust in management in Aqaba, Jordan.

A questionnaire survey was administered to collect data among the contractors Grade1 across Aqaba, Jordan. This research was designed as a quantitative study and data were collected at one point of time. In total, 311 questionnaires were returned and only 279 completed questionnaires to test the relationship between HPWPs and employee performances according to the ability, motivation and opportunity conceptualized framework. The partial least squares technique was adopted to test the proposed relationships.

The results present that extensive training, rewards based on performance and job security have a significant relationship with trust in management. Trust in management exerts partial mediation effects between HPWPs (extensive training, rewards based on performance and job security) and employee performance (creativity and innovation).

The findings of the study provide useful and original information to improve the overall performance of construction firms.

The objective of this research is to propose an immersive framework that integrates virtual reality (VR) technology with directives international safety training certification bodies to enhance construction safety training, which eventually leads to safer construction sites.

The adopted methodology combines expert insights and experimentation to maximize the effectiveness of construction safety training. The first step was identifying key considerations for VR models such as motion sickness prevention and adult learning theories. The second step was developing a game-like VR model for safety training, with multiple hazards and scenarios based on the considerations of the previous step. After that, safety experts evaluated the model and provided valuable feedback on its alignment with international safety training practices. Finally, the developed model is tested by senior students, where the testing format followed the Institution of Occupational Safety and Health (IOSH) working safely exam structure.

An advanced immersive VR safety training model was developed based on extensive lessons learned from the literature, previous work and psychology-informed adult learning theories. Model testing – through focus groups and hands-on experimentation – demonstrated significant benefit of VR in upgrading and complementing traditional training methods.

The findings presented in this paper make a significant contribution to the field of safety training within the construction industry and the broader context of immersive learning experiences. It also fosters further exploration into immersive learning experiences across educational and professional contexts.

The purpose of this paper is to critically review the literature on design thinking training to elucidate guidelines for best practices of design thinking training interventions.

The literature was reviewed, which outlined several themes that informed a series of recommendations for organizations considering developing design thinking training.

Process-based training, delivery activities and content, skills-based approach, delivery format, support for training and training evaluation were identified as key themes in the literature. These themes highlighted practical recommendations for developing design thinking training interventions. Findings also demonstrate current limitations in the literature.

Research on design thinking training is limited; therefore, recommendations for training should be applied carefully. The limited research points to a fruitful area for future research and development of design thinking training.

This paper suggests that researchers and practitioners should develop face-to-face or hybrid design thinking training interventions that follow the design thinking process and focus on the development of relevant skills, using interactive, user-focused and design visualization activities. Results suggest that adequate support for training should be provided, and outcomes of training should be empirically evaluated.

To the best of the authors’ knowledge, this paper is the first to review the design thinking training literature and provide general recommendations for both design thinking training development and design thinking research.

The paper aims to examine literature on the issues of the pilot shortage in the United States Air Force and the demographic diversity dilemma within the United States Air Force pilot community and how it relates to the National Defense Strategy. In addition, there is an examination of current initiatives designed to combat these issues.

The paper opted for an exploratory review of 90 sources from 2012 to 2023 to examine the pilot shortage and pilot diversity issues within the United States Air Force. Three theories, the theory of generative interactions, the theory of cognitive diversity and the identity theory, were examined in relation to the barriers to the pilot diversity issue.

The paper provides emergent insights from the literature into the growing pilot shortage and diversity disparity found within the United States Air Force pilot community. These issues were associated with many barriers, including geographic disparity, socioeconomic status, culture, education, mentorship and life balance.

The current initiatives examined are new and, as such, warrant future research. In particular, what are the long-term projections for the youth flight programs? An examination of the effectiveness of improving the pilot shortage and pilot diversity within the Air Force should be further scrutinized in the coming years as new cadets enter pilot training after accession.

This paper highlights a need to further study the effectiveness of youth flight programs and other United States Air Force initiatives in improving pilot numbers and diversity.

The aim of this article is the exploration of historical themes that formed education and training in public relations and corporate communication. Its timeline is from the early 1950s to the mid-1990s when university-level education became widespread. It also acknowledges recent initiatives to propose a Global Capability Framework for the field.

Archival material, primarily from the International Public Relations Association, was reviewed in order to understand the historic influences that have shaped public relations and corporate communication education in the, mainly, English-speaking world. This was compared with other sources such as journal, articles and other archives in the Germany, Spain, the United States, and the United Kingdom.

Three findings are offered from the archival research and analysis conducted for the article: (1) There was extensive debate over the structure of education between a skills-based approach that was taught as a minor or major stream in an undergraduate degree or graduate level study (Master's) in public relations theory and practice; (2) there was continuing tension between practitioner organizations and academics over the design, content and validation of educational programmes; and (3) there was little interest in the international harmonization of public relations education and training, despite extensive discussion.

No previous historical research has taken such a broad and international view of the development of education and training in public relations and corporate communication. The article also uses archival material that has become available in the past decade.

This paper provides practical advice for archaeologists and heritage specialists wishing to use ML approaches to identify archaeological features in high-resolution satellite imagery (or other remotely sensed data sources). We seek to balance the disproportionately optimistic literature related to the application of ML to archaeological prospection through a discussion of limitations, challenges and other difficulties. We further seek to raise awareness among researchers of the time, effort, expertise and resources necessary to implement ML successfully, so that they can make an informed choice between ML and manual inspection approaches.

Automated object detection has been the holy grail of archaeological remote sensing for the last two decades. Machine learning (ML) models have proven able to detect uniform features across a consistent background, but more variegated imagery remains a challenge. We set out to detect burial mounds in satellite imagery from a diverse landscape in Central Bulgaria using a pre-trained Convolutional Neural Network (CNN) plus additional but low-touch training to improve performance. Training was accomplished using MOUND/NOT MOUND cutouts, and the model assessed arbitrary tiles of the same size from the image. Results were assessed using field data.

Validation of results against field data showed that self-reported success rates were misleadingly high, and that the model was misidentifying most features. Setting an identification threshold at 60% probability, and noting that we used an approach where the CNN assessed tiles of a fixed size, tile-based false negative rates were 95–96%, false positive rates were 87–95% of tagged tiles, while true positives were only 5–13%. Counterintuitively, the model provided with training data selected for highly visible mounds (rather than all mounds) performed worse. Development of the model, meanwhile, required approximately 135 person-hours of work.

Our attempt to deploy a pre-trained CNN demonstrates the limitations of this approach when it is used to detect varied features of different sizes within a heterogeneous landscape that contains confounding natural and modern features, such as roads, forests and field boundaries. The model has detected incidental features rather than the mounds themselves, making external validation with field data an essential part of CNN workflows. Correcting the model would require refining the training data as well as adopting different approaches to model choice and execution, raising the computational requirements beyond the level of most cultural heritage practitioners.

Improving the pre-trained model’s performance would require considerable time and resources, on top of the time already invested. The degree of manual intervention required – particularly around the subsetting and annotation of training data – is so significant that it raises the question of whether it would be more efficient to identify all of the mounds manually, either through brute-force inspection by experts or by crowdsourcing the analysis to trained – or even untrained – volunteers. Researchers and heritage specialists seeking efficient methods for extracting features from remotely sensed data should weigh the costs and benefits of ML versus manual approaches carefully.

Our literature review indicates that use of artificial intelligence (AI) and ML approaches to archaeological prospection have grown exponentially in the past decade, approaching adoption levels associated with “crossing the chasm” from innovators and early adopters to the majority of researchers. The literature itself, however, is overwhelmingly positive, reflecting some combination of publication bias and a rhetoric of unconditional success. This paper presents the failure of a good-faith attempt to utilise these approaches as a counterbalance and cautionary tale to potential adopters of the technology. Early-majority adopters may find ML difficult to implement effectively in real-life scenarios.

Unlike many high-profile reports from well-funded projects, our paper represents a serious but modestly resourced attempt to apply an ML approach to archaeological remote sensing, using techniques like transfer learning that are promoted as solutions to time and cost problems associated with, e.g. annotating and manipulating training data. While the majority of articles uncritically promote ML, or only discuss how challenges were overcome, our paper investigates how – despite reasonable self-reported scores – the model failed to locate the target features when compared to field data. We also present time, expertise and resourcing requirements, a rarity in ML-for-archaeology publications.

Previous literature has identified human resources as a key source of competitive advantage in organizations of all sizes. However, Small and Medium-sized Enterprises (SMEs) face difficulty in comprehensively implementing all recommended Human Resource Management (HRM) functions. In this study, we shed light on the field of HRM in SMEs by focusing on the context of Greek Small and Medium-sized Hotels (SMHs), which represent a dominant private sector employer across the country.

Using a fuzzy-set qualitative comparative analysis (fsQCA) and 34 in-depth interviews with SMHs' owners/managers, we explore the HRM conditions leading to high levels of performance, while taking into consideration the influence of internal key determinants.

We uncover three alternative successful HRM strategies that maximize business performance, namely the Compensation-based performers, the HRM developers and the HRM investors. Each strategy fits discreet organizational characteristics related to company size, ownership type and organizational structure.

To the best of the authors' knowledge this is among the first empirical studies that examine different and equifinal performance-enhancing configurations of HRM practices in SMHs.