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Applying resource-based view and the configurational approach theory, this study seeks to understand the moderating role of age and gender between human resource practices and employee competencies relationship.

43 food processing firms of India participated in the study. Applying multilevel approach, the responses of 295 human resource managers and 3,557 employees were used for the analysis.

The human resource practices–employee competencies relationship was stronger in the case of young employees. Furthermore, the relationship was better in case of male employees over female employees. The results urge for greater attention toward age and gender diversity issues while tailoring human resource practices for enhancing employee skills. This article contributes the human resource management literature by exploring the role of age and gender, which has been used as the control variables as the moderating variables for governing the human resource practices–employee competencies relationship.

Special focus can be placed on extensive custom in-house training and development activities. Proper division of work can be done for new employees and experienced employees depending upon their learning capabilities. The firms can do so by either implementing formal or informal organizational structures to achieve full gains. Firms should focus largely on narrowing the development practices adopted for diverse age groups of workforce population. The four practices proposed by the Organization for Economic Cooperation and Development (2006) for ensuring effectiveness of development practices and its impact on old age employee effectiveness and attitude should be put in practice.

The originality of this study lies in its exploration of the intricate interplay among age, gender and human resource practices in shaping employee competencies. By understanding how these factors interact within the human resource practices–employee competencies framework, this research offers a unique perspective on the evolving workforce dynamics. It goes beyond the conventional human resource management strategies to uncover nuanced insights, shedding light on tailored approaches that consider the specific needs and aspirations of diverse employees. This innovative perspective contributes to a more inclusive, efficient and adaptable work environment, enriching both the academic understanding of human resources and the practical implementation of strategies for contemporary organizations.

Multinational business deliver value via multiple sites with similar operational capacities. The age of the Fourth Industrial Revolution (4IR) delivers significant opportunities for the deployment of digital tools for business optimization. Therefore, this study aims to study the Industry 4.0 implementation for multinationals.

The key objective of this research is multi-site systems integration using a reproducible, modular and standardized “Cyber Physical System (CPS) as-a-Service”.

A best practice reference architecture is adopted to guide the design and delivery of a pioneering CPS multi-site deployment. The CPS deployed is a cloud-based platform adopted to enable all manufacturing areas within a multinational energy and petrochemical company. A methodology is developed to quantify the system environmental and sustainability benefits focusing on reduced carbon dioxide (CO₂) emissions and energy consumption. These results demonstrate the benefits of standardization, replication and digital enablement for multinational businesses.

The research illustrates the ability to design a single system, reproducible for multiple sites. This research also illustrates the beneficial impact of system reuse due to reduced environmental impact from lower CO₂ emissions and energy consumption. The paper assists organizations in deploying complex systems while addressing multinational systems implementation constraints and standardization.

Social media marketing has become a powerful strategic tool for many brands, but scholarly research in this domain is still in its infancy. This study aims to examine the effects of social media marketing activities on consumer online impulse buying intentions via brand resonance and emotional responses by incorporating the direct and moderating effects of social network proneness toward fashion retail brands.

By using snowball sampling, this study recruited 441 netizens (who were using fashion retail brands) and obtained their responses through an online survey. Structural equation modeling was applied to 394 responses for analysis.

The findings discovered that social media marketing activities significantly influenced brand resonance, consumer emotional responses and online impulse buying intentions. Likewise, brand resonance and emotional responses were positively associated with online impulse buying intentions and acted as decisive mediators. Social network proneness’s direct and moderating effects significantly increased consumer online impulse-buying intentions toward fashion retail brands.

This study provides recommendations to retail managers for creating and executing brand positioning, segmenting and targeting strategies to enhance consumers’ intentions for engaging in online impulsive purchases for fashion brands.

This original research contributes to the branding literature and stimulus–organism–response theory by focusing on social media marketing activities, brand resonance, emotional responses, social network proneness and consumer online impulse buying intentions toward fashion retail brands.

This study aims to critically examine the effects of COVID-19 social discourses and policy decisions specifically on older adult volunteers in the UK, comparing the responses and their effects in England, Scotland, Wales and Northern Ireland, providing perspectives on effects of policy changes designed to reduce risk of infection as a result of COVID-19, specifically on volunteer involvement of and for older adults, and understand, from the perspectives of volunteer managers, how COVID-19 restrictions had impacted older people’s volunteering and situating this within statutory public health policies.

The study uses a critical discourse approach to explore, compare and contrast accounts of volunteering of and for older people in policy, and then compare the discourses within policy documents with the discourses in personal accounts of volunteering in health and social care settings in the four nations of the UK. This paper is co-produced in collaboration with co-authors who have direct experience with volunteer involvement responses and their impact on older people.

The prevailing overall policy approach during the pandemic was that risk of morbidity and mortality to older people was too high to permit them to participate in volunteering activities. Disenfranchising of older people, as exemplified in volunteer involvement, was remarkably uniform across the four nations of the UK. However, the authors find that despite, rather than because of policy changes, older volunteers, as part of, or with the help of, volunteer involving organisations, are taking time to think and to reconsider their involvement and are renewing their volunteer involvement with associated health benefits.

Working with participants as co-authors helps to ensure the credibility of results in that there was agreement in the themes identified and the conclusions. A limitation of this study lies in the sampling method, as a convenience sample was used and there is only representation from one organisation in each of the four nations.

The paper combines existing knowledge about volunteer involvement of and for older adults.

Our proposed machine learning model contributes to improving the quality of Hire by providing a more nuanced and comprehensive analysis of candidate attributes. Instead of focusing solely on obvious factors, such as qualifications and experience, our model also considers various dimensions of fit, including person-job fit and person-organization fit. By integrating these dimensions of fit into the model, we can better predict a candidate’s potential contribution to the organization, hence enhancing the Quality of Hire.

Within the scope of the investigation, the competencies of the personnel working in the IT department of one in the largest state banks of the country were used. The entire data collection includes information on 1,850 individual employees as well as 13 different characteristics. For analysis, Python’s “keras” and “seaborn” modules were used. The Gower coefficient was used to determine the distance between different records.

The K-NN method resulted in the formation of five clusters, represented as a scatter plot. The axis illustrates the cohesion that exists between things (employees) that are similar to one another and the separateness that exists between things that have their own individual identities. This shows that the clustering process is effective in improving both the degree of similarity within each cluster and the degree of dissimilarity between clusters.

Employee competencies were evaluated within the scope of the investigation. Additionally, other criteria requested from the employee were not included in the application.

This study will be beneficial for academics, professionals, and researchers in their attempts to overcome the ongoing obstacles and challenges related to the securing the proper talent for an organization. In addition to creating a mechanism to use big data in the form of structured and unstructured data from multiple sources and deriving insights using ML algorithms, it contributes to the debates on the quality of hire in an entire organization. This is done in addition to developing a mechanism for using big data in the form of structured and unstructured data from multiple sources.

Drawing on the conservation of resources theory, this study examines how proactive skill development (PSD) influences job performance and mediating and moderating mechanisms underlying the above relationship.

Data were collected from a sample of 261 full-time workers in three waves, spaced by a six-week interval (Time 1, N = 360; Time 2, N = 320; Time 3, N = 261).

The results confirmed that career stress mediated the relationship between PSD and job performance. Additionally, high career decidedness strengthened this negative relationship between stress and performance. Furthermore, career decidedness significantly moderated the indirect PSD–performance relationship via career stress, accentuating the indirect effect when decidedness is higher.

This study sheds light on the important role of proactive skills development in influencing job performance and what factors can affect this relationship. It offers practical implications by highlighting how targeted training can boost employees' proactivity and performance.

This study aims to provide an overall framework that connects and explains a macro-perspective of the findings from the five studies of this special issue. Through this, we aim to answer two main questions: How can Lean and Industry 4.0 be integrated, and what are the outcomes for workers from such integration?

The special issue received 64 papers that were evaluated in multiple stages until this final sample of five papers that describe different facets of the integration between Lean and Industry 4.0 and their relationship with worker activities. In this introduction, we review the main findings of these five studies and propose an integrative view and associated propositions. A discussion provides directions to advance the field further.

The framework shows that when Lean and Industry 4.0 are integrated, companies will face two types of tensions, dialectical and paradoxical, which require different managerial approaches. By managing such tensions, the Lean-Industry 4.0 integration can help improve social performance, as well as develop systematic problem-solving and cumulative learning capabilities. Five important themes for this field of research are outlined: the importance of work routines, legitimation, competence, sense and mental flexibility.

This study brings a new theoretical perspective to the integration of Lean with Industry 4.0-related digital technologies. The results go beyond the usual view of improving operational performance and dig into the effects on workers. It also shows that the integration process relies on and can enhance human capabilities such as learning and problem-solving.

Perceptions of ageing towards the self and towards others can positively and negatively impact an older adult’s mental wellbeing. This paper aims to consolidate literature examining the relationship between perceptions of ageing and depression in older adults to inform both practice and policy for older adult mental health services.

Quantitative research articles examining perceptions of ageing and depression in older adults were identified through searches on three electronical databases, alongside forward and backwards citation searches. A total of 14 articles involving 31,211 participants were identified.

Greater negative attitudes towards ageing were associated with higher levels of depressive symptoms and greater positive attitudes towards ageing were associated with lower levels of depressive symptoms or higher levels of happiness. However, the causal direction of this relationship could not be determined. Studies demonstrated that perceptions of ageing also act as a moderator in the relationship between depression and health status, hopelessness and personality traits. Future research should attempt to examine the relationship between perceptions of ageing and depression in older adults to attempt to identify the causal direction of this relationship.

This is the only systematic review the authors are aware of consolidating literature which explores the relationship between older adults’ perceptions of ageing and depression. It is hoped that these findings will be able to inform both policy and practice to improve older adults’ care and support for depression.

This paper aims to identify the basis of the technological anxiety phenomenon by defining the differences and similarities in terms of barriers of the implementation of Industry 4.0 technologies across industrial processing sector.

This paper presents a qualitative, exploratory research, and the authors apply the cross-case study method. The study is based on interviews with representatives of 11 medium-sized and large companies from industrial processing sector; specifically, the authors focus on three industries: automotive, food and furniture.

The research showed that there are similarities as well as differences in terms of identified barriers between individual industries. Taking into account the various dimensions of technological anxiety, similarities are visible, in particular, in the case of Internal processes and infrastructure and human resources, while in the other two dimensions, i.e. strategic planning and standards and security, differences between the sectors were noted.

The developed list of barriers can be a starting point for middle and senior managers of manufacturing companies to understand the sources of technological anxiety. The planning and introducing preventive and protective tools during Industry 4.0 implementation may reduce the occurrence of technological anxiety and thus ensure a smoother adoption of technologies 4.0, while respecting the organizational culture.

This work contributes to in-depth understanding of multifaced technological anxiety phenomenon. This paper classifies dimensions of existing barriers, increases the awareness on the difficulties during transformation process and, thus enables the improvement of the use of company’s internal potential.

Building information modelling (BIM) has been established in the literature as a successful platform that creates an intelligent virtual model for processing data from conceptual design through construction to operational stage of a facility. However, its adoption for facilities management (FM) provision in Nigeria has been slow due to inherent barriers. The aim of this paper is to (1) assess and categorise using factor analysis BIM for FM barriers and (2) model the barriers using stakeholders' personal/professional attributes.

Anchored on quantitative research design, 205 copies of structured questionnaire were distributed to key stakeholders and facilities managers in Nigeria's three strategic cities while 135 valid responses were received giving a response rate of 65.8%. Data collected were analysed using descriptive statistics while multiple regression analysis was used to model the barriers. Kruskal Wallis test was used to test the only hypothesis postulated for the study.

The study established lack of awareness of BIM for FM, poor supporting infrastructure for Internet services, and lack of education and training as the top three rated barriers militating against adoption of BIM for FM in Nigeria while corruption, widespread mistakes and errors and cultural issues were established as the three least rated barriers. Besides, findings also established eight underlying factors that explained 23 barrier factors used for the study which were subsequently used to develop eight regression models. In effect, gender, professional affiliation, organisation, experience, education, expertise, BIM for FM project type, and location were found to statistically predict the 8 extracted factors driving perceived barriers of BIM for FM adoption in Nigeria.

The study has provided a framework of barrier factors to help stakeholders identify specific barriers for which appropriate measures can be taken to ameliorate consequences of the perceived barriers. Meanwhile, an improved and rejuvenated advocacy on inherent benefits of BIM for facilities management by frontline stakeholders could potentially steer up interests and increased participation of stakeholders on BIM for FM.

The unique study developed the first ever regression model that links BIM for FM barriers to professional attributes of facilities management stakeholders in Nigeria.