Search results

The purpose of this study was to investigate the provincial-level systems and mechanisms to develop health volunteers to improve the health of the immigrant workforce in Thailand.

This qualitative study obtained data from document research, in-depth interviews with 58 people involved at policy and provincial levels working to develop health volunteers to improve the health of the immigrant workforce. Data were collected from May–October 2017; then the content of the conceptual framework was analyzed, the research objectives were examined and summary and induction analysis interpreted data from documents, observations and interviews.

Thailand has four systems for developing health volunteers to improve the health of the immigrant workforce: recruitment, training and knowledge management, welfare and motivational and financial and other supportive resources. Development is driven through the mechanisms of the Provincial Public Health Office with Non Governmental Organizations (NGOs) and network partners. The health volunteer development exhibits two patterns: developing migrant workers to become migrant health volunteers and developing village health volunteers to perform health care for the immigrant workforce. All development patterns mainly rely upon the regular operating budget, which is often inadequate. Frequently, some provinces make attempts to seek other funding sources. In fact, health volunteer development is subjected to local authorities of the four provinces whose systems and mechanisms of development differ from one another.

The findings from this study could help develop health volunteers to significantly improve the health of the immigrant workforce in the Thai health service system.

In today’s digital economy, it is very important to cultivate digital professionals with advanced interdisciplinary skills. The purpose of this paper is that universities play a vital role in this effort, and research teams need to use the synergistic effect of various educational methods to improve the quality and efficiency of personnel training. For these teams, a powerful evaluation mechanism is very important to improve their innovation ability and the overall level of talents they cultivate. The policy of “selecting the best through public bidding” not only meets the multi-dimensional evaluation needs of contemporary research, but also conforms to the current atmosphere of evaluating scientific and technological talents.

Nonetheless, since its adoption, several challenges have emerged, including flawed project management systems, a mismatch between listed needs and actual core technological needs and a low rate of conversion of scientific achievements into practical outcomes. These issues are often traced back to overly simplistic evaluation methods for research teams. This paper reviews the literature on the “Open Bidding for Selecting the Best Candidates” policy and related evaluation mechanisms for research teams, identifying methodological shortcomings, a gap in exploring team collaboration and an oversight in team selection criteria.

It proposes a theoretical framework for the evaluation and selection mechanisms of research teams under the “Open Bidding for Selecting the Best Candidates” model, offering a solid foundation for further in-depth studies in this area.

Research progress on the Evaluation Mechanism of Scientific Research Teams in the Digital Economy Era from the Perspective of “Open Bidding for Selecting the Best Candidates.”

This study aimed to investigate the mechanisms of knowledge brokering and role crafting structures that promote the active engagement of older workers at work.

The respondents were workers in Japan aged 55–64 years. A two-wave panel survey was conducted. The first and second survey waves included 1,527 and 1,467 respondents, respectively.

The results showed that knowledge brokering positively influenced work engagement directly and indirectly. In the three dimensions of role crafting, cognitive and task crafting had a positive effect on work engagement.

This study focused on older workers in Japan. Therefore, it is necessary to verify whether the same effect is observed in countries other than Japan or among younger workers.

On an individual level, older workers should aim to keep acquiring new information inside and outside the organisation. On an organisational level, it is effective to increase opportunities for older workers to craft their work according to the socioemotional selectivity and selection optimisation and compensation theories.

This study reveals that knowledge brokering and cognitive crafting in role crafting have an important influence on the work engagement of older workers. Additionally, this study clarifies the impact of job crafting on older workers not only from the perspective of resource crafting to achieve person-job fit but also from the perspective of reframing perceptions through cognitive crafting in role crafting. These findings enable a clearer understanding of the relationship between role crafting and knowledge brokering, as well as the socioemotional selectivity and selection optimisation and compensation theories.

In this paper, we depart from extant conceptualisations of knowledge translation mechanisms to examine projects as a way to achieve effective knowledge transfer. Our empirical analysis focused on a university–industry research project in the automotive industry.

The empirical analysis was based on a qualitative investigation. We analysed material collected within a research project involving a partnership between two universities and Fiat-Chrysler Automotive (FCA), a multi-brand auto manufacturer with a product range covering several different market segments. We used three data collection techniques: internal document analysis, participant observation and semi-structured interviews.

Our findings show that, in a U-I research project, goals represent a key dimension to support knowledge translation. Defining the goal implies an ongoing negotiation process, where researchers and company employees work together, in order to converge towards a shared meaning of the goal. In this sense, goal orientation and goal-based interaction have significant implications for knowledge translation processes.

Studies to date have focussed on the concept of knowledge translation as a way to contextualise the transfer from the source of knowledge to the receiver and to interpret the knowledge to be exchanged. This study expands the understanding of knowledge translation mechanisms in university–industry research settings. It investigates the concept of projects as powerful knowledge translation mechanism in a dynamic and longitudinal perspective. Our contribution provides insight, reflecting on how the use of projects may represent a way to facilitate knowledge transfer and build up new ideas and solutions.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

Supply chain (SC) professionals and their competence play a key role in creating value and competitive advantage for companies. A considerable amount of this competence is developed at work, but little is known about how this takes place. Drawing on constructivist learning theory, the authors investigate how SC professionals develop their competence at work.

The study takes off from a theoretical framework of workplace learning mechanisms, followed by a series of in-depth interviews with an expertise panel of profoundly competent and experienced SC professionals.

The results provide detailed insights into the learning process of SC professionals. The key findings show that SC professionals use a wide range of learning mechanisms throughout their careers, and that the contribution and complexity of these mechanisms differ and change dynamically with seniority. The findings also show that learning mechanisms should not be viewed as isolated phenomena, but closely related to every-day SCM work as well as learning attitude.

By conceptualizing learning as a process, and congregating the fragmented literature into a framework of workplace learning mechanisms, this research provides a theoretical reference point for future studies. The empirical findings bring a new level of detailed knowledge on how SC professionals learn at work.

The results can assist SC professionals, HR managers and academic program leaders in their quest to develop competence in the field of SCM.

This paper makes a unique contribution to the human aspects of SCM literature by presenting the first study that investigates in depth the crucial but complex process of how workplace learning takes place for SC professionals in practice.

Based on an exploratory case-based approach, the purpose of this paper is to open the KM black box and examine the relationships that link knowledge management (KM) inputs (i.e. knowledge resources and KM practices) via knowledge processes to KM performance. This paper aims to identify the underlying mechanisms and explain how KM performance is enabled.

This in-depth case study conducted at a medium-sized consultancy in the supply chain management industry empirically examines knowledge flows to uncover the relationships between KM inputs, knowledge processes and KM performance. We adopt the viable system model (VSM) as a theoretical lens to identify KM mechanisms.

By identifying six KM mechanisms, we contribute to the theoretical understanding of how KM inputs are interconnected and lead to KM performance via knowledge processes.

Based on the insights gained, we provide propositions that organizations should consider in designing viable KM. Our findings help organizations in understanding their KM with the help of knowledge flow analysis and identifying how critical KM elements are interconnected.

This study aims to investigate how two collaborative methods – selection and synthesis – influence knowledge convergence when people articulate a new strategic direction driving transformation within the organization.

The study is based on a longitudinal field experiment developed in four organizations involving 82 employees over a three-month process. Inspired by dynamics governing flocks as complex adaptive systems, selection and synthesis have been separately used in two sets of companies. Primary and secondary data have been largely collected and analyzed throughout the whole process.

This study describes how the two alternative methods differently influenced two kinds of knowledge convergence. While selection triggers a general and static knowledge convergence and the propagation of individual knowledge over time, synthesis fosters a local and dynamic knowledge convergence where individuals tend to propagate knowledge generated collectively.

This research offers insights into understanding the influence of alternative collaborative methods on the creation and propagation of knowledge when people are converging toward a new strategic direction. From a theoretical perspective, it contributes to complex adaptive system theory, highlighting the role of knowledge convergence and emergence through collaboration.

This research offers insights to managers who deal with the complexity of the engagement of different stakeholders during collaborative processes, offering some actionable takeaways to foster knowledge convergence by alternatively employing selection and synthesis.

This paper contributes to the management and social information processing literature emphasizing the role of knowledge convergence emerging from the complex interactions among multiple stakeholders.

Organisations must build resilience to be able to deal with disruptions or non-routine events in their supply chains. While learning is implicit in definitions of supply chain resilience (SCRes), there is little understanding of how exactly organisations can adapt their routines to build resilience. The purpose of this study is to address this gap.

This paper is an in-depth qualitative case study based on 28 interviews across five companies, exploring learning to build SCRes.

This study uncovers six learning mechanisms and their antecedents that foster SCRes. The learning mechanisms identified suggest that through knowledge creation within an organisation and knowledge transfer across the supply chain and broader network of stakeholders, operating routines are built and/or adapted both intentionally and unintentionally during three stages of a supply chain disruption: preparation, response and recovery.

This study shows how the impact of a supply chain disruption may be reduced by intentional and unintentional learning in all three disruption phases. By being aware of the antecedents of unintentional learning, organisations can more consciously adapt routines. Furthermore, findings highlight the potential value of additional attention to knowledge transfer, particularly in relation to collaborative and vicarious learning across the supply chain and broader network of stakeholders not only in preparation for, but also in response to and recovery from disruptions.

This study contributes novel insights about how learning leads both directly and indirectly to the evolution of operating routines that help an organisation and its supply chains to deal with disruptions. Results detail six specific learning mechanisms for knowledge creation and knowledge transfer and their antecedents for building SCRes. In doing so, this study provides new fine-grained theoretical insights about how SCRes can be improved through all three phases of a disruption. Propositions are developed for theory development.

This paper aims to identify empirically the influence of learning mechanisms provided by organizations on knowledge sharing in the organizational environment.

A quantitative study was developed in which a sample of 268 individuals from civil and military organizations of the Federal Direct Administration was researched. The questionnaire used was composed of the Organizational Learning Mechanism Scale, which was adapted at the time of the present study, in addition to a scale on knowledge sharing, which was developed within the scope of this research. After performing the factorial analysis for both scales, a canonical correlation analysis was performed between the group of variables associated with the learning mechanisms (independent variables) and the group of variables on knowledge sharing (dependent variables).

The results found in the canonical correlation analysis indicate that the learning mechanisms are responsible for explaining 35 per cent of the variance (R² = 0.352) of the group of variables on knowledge sharing.

The findings of this research can help the researched organizations to increase the knowledge management actions, mainly in relation to the actions that favor social interaction among the individuals in the work environment, making possible the exchange of knowledge and experiences in the internal organizational context, and exploring in a positive way actions related to internal acquisition.

The deeper knowledge about the relationship between organizational actions promoted by top management and knowledge support decision-making in the organizational environment regarding contextual factors that influence social interaction between individuals. In relation to the sharing of knowledge, a high correlation of knowledge absorption and reproduction aspects with the knowledge sharing phenomenon was perceived, so that the possibility of organizations thinking in ways that provide the individual with formal and informal environments can be foreseen.

The main contributions of this research are to measure the intensity of the relationship between learning mechanisms and knowledge sharing; and to test the predictive effect of learning mechanisms on knowledge sharing. Regarding the methodological aspects, it was opportune to approach the phenomenon through a little used lens in the context of administration research: the analysis of canonical correlation, which represents another look at the influence of the actions of the top management and the interaction of individuals. The discussions and the data analysis carried out in this research allow us to envisage significant contributions of this work to the analysis and theoretical refinement of the study of the variables treated.