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The purpose of this paper is to empirically study transfer mechanisms of technological knowledge, and to explore the interplay among the factors that influence the choice of a mechanism.

This paper reports on a qualitative case study designed to explore the reasons underlying the selection of intra-organizational knowledge transfer mechanisms. This research was carried out as an exploratory case study, which allowed one to observe the phenomenon in a natural setting.

The results of the present study indicate the interplay between the factors, and link the factors in a sequence that help decide a mechanism. A decision to select a mechanism depends upon several variables; some of them override others, others are interlinked, and sometimes there is a causal link.

It is based on a sample of employees that may not be representative of the broader population. Since the samples were drawn only from a MNC, the results may not be generalised. The case study method which was employed in this research does not permit the generalisation of the results.

The knowledge transfer literature has discussed the mechanisms used to transfer technological knowledge, but has failed to adequately address the rationale behind the selection of an appropriate knowledge transfer mechanism. The extant literature has isolatedly identified factors that impact on the choice of knowledge transfer mechanism. These issues are not effectively addressed in prior research. The findings are summarized diagrammatically in the form of a decision tree which provides a conceptualization of the decision processes involved in the selection of the medium for knowledge transfer.

Based on definition and characteristic analysis, this paper seeks to propose a formation mechanism of knowledge rigidity, which is constituted by the effects of three precipitating factors: time‐effectiveness of knowledge, reinforcing effectiveness, and sunk cost effect in knowledge selection mechanism.

By presenting knowledge time‐effectiveness model, reinforcing effectiveness model, and knowledge selection mechanism, the paper theoretically analyzes firms' rigid behavior of knowledge application. Theories of increasing returns and sunk cost are introduced to explain the formation process of knowledge rigidity in firms. Two cases are presented to analyze the knowledge rigidity in industrial firms basing on the proposed models and mechanism.

First, the lifecycle of knowledge rigidity is dynamically defined by knowledge time‐effectiveness. Second, the degree of rigidity and firm's dependence on specific knowledge are enhanced by reinforcing effectiveness during the process of application. At the end of the life cycle, the sunk cost mainly hinders a firm's decision making to replace ineffective knowledge.

Quantitative research is needed to further explore the formation mechanism of knowledge rigidity and to present operational approaches for practitioners. The proposed models and mechanism are useful for understanding the knowledge rigidity and analyzing its formation mechanism in firms.

This paper provides theoretical support to realize knowledge rigidity in KM practice. Three indicators were proposed to evaluate the rigidity and action suggestions were given to help control knowledge rigidity in firms.

Causal analysis models and a formation mechanism are proposed to show how knowledge rigidity forms.

This study aims to not only develop measurements of preferential attachment and homophily mechanisms based on their definitions and network theory but also examine the associations among these network mechanisms, community commitment, knowledge sharing and community citizenship behavior.

In total, 250 valid questionnaires are collected to examine the hypothesized associations. These hypotheses are examined by using partial least squares structural equation modeling.

The findings reveal both mechanisms are beneficial to develop new entrants’ emotional attachment to a virtual community, thereby motivating knowledge sharing and community altruistic behavior. The results contribute some practical and theoretical implications that are very helpful for the conceptualization of network mechanisms, community development, relationship management and incentives for extra-role behavior.

The literature on the link between network selection mechanisms and knowledge sharing remains unknown. This study is the pioneer to disclose this unknown association and examine the impacts of preferential attachment and homophily network mechanisms.

The paper aims to analyse entrepreneurs' expectations regarding future growth by analysing the relationship between information flows from networks and the perceived risk of decisions associated with the future size of a firm.

The paper's main proposition is that growth expectations might be the outcome of superior judgment stemming from the privileged information derived from networks. To provide evidence in support of this hypothesis, a sample selection model was estimated using a two‐step estimation procedure. Cross‐section questionnaire data were used in the empirical analysis.

Analysis indicates that networks are indeed information mechanisms; however, such information should be specific to problem‐solving firm processes. Better‐informed entrepreneurs are those that foresee higher growth in the future; yet, they are not blocked in only local networking.

The small sample size might be viewed as a limitation; yet, the very satisfactory fit of the estimated model allows empirical findings to be a useful comparison with future evidence in the field.

Evidence is provided on the role of inter‐firm contacts and relationships as a mechanism able to assist entrepreneurs in better assessing and even reduce the risk and uncertainty associated with their present and future decisions regarding firm growth.

The paper provides evidence on the factors affecting expected growth rates, while it explicitly formulates and tests the hypothesis that expectations regarding growth might be the outcome of superior judgment stemming from the privileged information derived from networks.

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.

The purpose of this paper is to theoretically develop and empirically explore knowledge absorption, combination and desorption within and between organizations.

On the basis of knowledge-based view and absorptive capacity, the authors have conducted a multiple-case study to develop a theoretically grounded and empirically supported model of intra- and inter-firm knowledge cycles.

Firms identify their knowledge gaps and stocks, both tacit and explicit, undertaking efforts to fill the latter and maximize the value of the former. The paper finds that knowledge exploration, integration and exploitation both within the firm and between firms relies on absorptive, combinative and desorptive capacities. Further, as such capacities are organizationally expensive to maintain, firms will often emphasize one capacity over the other and focus either internally or externally to meet organizational goals.

While there is extensive research into absorptive capacity and some into combinative capacity, there is little empirical investigation of desorptive capacity and none into the integration of the three concepts; this paper seeks to fill that gap. Moreover, the resulting novel integrative model allows managers and researchers to identify the various capacities in use and their applications within the firm and between firms.

The purpose of this paper is finding the optimal geometric parameters and developing of a method for optimizing a light unmanned aerial vehicle (UAV) wing, maximizing, at the same time, its endurance with the assumed parameters of aircraft mission.

The research is based on the experience gained by the author’s contribution to the project of building medium-altitude, long-endurance class, light UAV called “Samonit”. The author was responsible for the structure design, wind tunnel tests and flight tests of the “Samonit” aircraft. Based on the experience, the author was able to develop an optimization process considering various disciplines involved in the whole aircraft design topics such as aerodynamics, flight mechanics, structural stiffness and weight, aircraft stability and maneuverability. The presented methodology has a multidisciplinary nature, as in the process of optimization both aerodynamic aspects and the influence of wing geometric parameters on the wing structure and weight and the aircraft payload were taken into account. The optimal wing configuration was obtained using the genetic algorithms.

As a result, a set of wing geometrical parameters has been obtained that allowed for achieving twice as long endurance as compared with the initial one.

Using the methodology presented in the paper, an aircraft designer can easily find the optimum wing configuration of a designed aircraft, satisfying the mission requirements in a best way.

An original procedure has been developed, based on the actual design, wind tunnel tests and numerical calculations of “Samonit” aircraft, enabling the determination of optimum wing configuration for a small unmanned aircraft.

The role of inter-organizational knowledge mechanisms (IOKMs) in learning networks is increasing so that the competition of business networks in providing innovations is highly dependent on the effective selection and application of these mechanisms. This study aims to argue that recognizing the classification of IOKMs and understanding their impact on networking capability (NC) makes the selection of mechanisms more effective.

With a systematic review of literature, a comprehensive list of IOKMs, their main characteristics and NCs have been extracted. The authors have used a focus group for data gathering and a hybrid multi-layer decision-making approach for data analysis. Finally, the impact of IOKMs on NC was determined.

By implementing a multi-layer decision-making approach, four categories of IOKMs including person-to-person, co-creation, team-oriented and informational are illustrated and their effects of NC are determined. Therefore, the findings of this research provide latecomer firms (LCFs) managers with a clear framework for selecting IOKMs.

The literature review shows that the number of knowledge mechanisms, especially their inter-organizational types, is increasing. It has made it difficult for LCFs managers to select effective and efficient mechanisms. Most of these mechanisms are listed, and few studies have classified them. Besides, research shows that fewer studies have investigated how IOKMs relate to NC. Furthermore, most studies on IOKMs have been conducted in the context of leading firms and LCFs have been neglected.

Complex cost structures and multiple conflicting objectives make selecting an appropriate cloud service difficult. The purpose of this study is to propose a novel group consensus decision making method for cloud services selection with knowledge deficit by trust functions.

This article proposes a knowledge deficit-based multi-criteria group decision-making (MCGDM) method for cloud-service selection based on trust functions. Firstly, the concept of trust functions and a ranking method is developed to express the decision-making opinions. Secondly, a novel 3D normalized trust degree (NTD) is defined to measure the consensus levels. Thirdly, a knowledge deficit-based interactive consensus model is proposed for the inconsistent experts to modify their decision opinions. Finally, a real case study has been carried out to illustrate the framework and compare it with other methods.

The proposed method is practical and effective which is verified by the real case study. Knowledge deficit is an important concept in cloud service selection which is verified by the comparison of the proposed recommended mechanism based on KDD with the conventional recommended mechanism based on average value. A 3D NTD which considers three values (trust, not trust and knowledge deficit) is defined to measure the consensus levels. A knowledge deficit-based interactive consensus model is proposed to help decision-makers reach group consensus. The proposed group consensus model enables the inconsistent decision-makers to accept the revised opinions of those with less knowledge deficit, rather than accepting the recommended opinions averagely.

The proposed a knowledge deficit-based MCGDM cloud service selection method considers group consensus in cloud service selection. The concept of knowledge deficit is considered in modeling the group consensus measuring and reaching method.

Although previous research has reached an agreement that finding appropriate alliance partners and reducing selection uncertainty are important for achieving high alliance performance, it has not explored (1) how organizations reduce selection uncertainty, (2) what mechanism enables organizations to do so, and, more generally, (3) how organizations form alliances. This research examined these research questions by conducting fieldwork at 20 biopharmaceutical organizations in the Untied States. I identified three mechanisms for reducing selection uncertainty, including the (1) relational, (2) internal, and (3) contextual mechanisms. One of the findings implies that alliances do not always emerge out of embedded ties, and that there exist variations in organizational usage and reliance on ties and personal rapport in constructing interorganizational networks.