Transferring new dynamic capabilities to SMEs: the role of ONERA – the French Aerospace LabTM in promoting asymmetries management

The technology transfer process between a public laboratory and a company has been the subject of many publications and has been widely discussed in economic theory. This paper highlights several newly identified asymmetries occurring between the different agents taking part in the process, dealing specifically with the aerospace and defense sectors in France. These specificities concern the characteristics, capabilities and competencies (the ‘capacities') of French SMEs and public research laboratories. The theoretical corpus of the article draws partly upon the analyses of ‘dynamic and interactive capabilities' (and competencies), and for the rest upon empirical sources, being based on the recent experience of one of the most dynamic Technology Transfer Offices (TTOs) in France: the case of ONERA (the National Office for Aerospace Studies and Research) and its dyadic relations with the SMEs. In such a cooperative, interactive innovation process, we will argue that certain collaborative tools or practices emerge, aimed at reducing information asymmetries or acting as compensation mechanisms for other types of asymmetries between the partners at a microeconomic level; especially in France where there is a gap between the public R&D laboratories and the SMEs in terms of Technology Readiness Levels (TRLs). Some of these compensation mechanisms, particularly those related to the knowledge economy, could be adapted and reshaped for agents engaged in R&D and innovation in various other sectors, perhaps inducing positive amplification effects on innovation behavior, and thereby on economic growth at the macroeconomic level within the “national innovation system”. This research work initiated by the author further to his economic research works on “innovation actors' asymmetries” (Paun, F., 2009) and “hybridizing tendency of the innovation approaches” (Paun, F., 2010) is based on the empirical study about eighty SMEs partners of ONERA coordinated by Florin Paun as Deputy Director in charge with Industrial Innovation at ONERA in order to better understand the barriers perceived inside this relationship and with the aim to envisage systemic solutions for accelerating innovation. A specific questionnaire has been developed by Florin Paun and more then forty interviews have been thus conducted with scientists and industrial representatives involved in direct collaborations linked to technology or knowledge transfer.French SMEs, technology transfer, information asymmetries, dynamic capabilities, innovation systems

The role of crop production clubs in technology transfer

Non-Peer ReviewedThis study was undertaken to determine if crop production club members represent an adopter category of the adoption diffusion theory as outlined by the literature, to obtain a more detailed description of the characteristics of the crop production club members and how they relate to the adopter categories and to determine the role crop production clubs play in the technology transfer process. A telephone survey was conducted using two groups, one selected from crop production clubs that had been organized for more than five years and the other a stratified random sample of non-club farmers in the surrounding area to the clubs. The questionnaire was designed to obtain information about innovative cropping practices, as well as demographic data, personal characteristics and communication behavior. A total of 38 crop production club members and 28 non-club farmers were contacted between April 22 and May 10, 1991. The results of the study found that the characteristics exhibited by crop production club members were similar to those outlined in the adoption-diffusion theory for early adopters. Therefore crop production club members fit into the adoption-diffusion process as early adopters. Crop clubs use demonstrations as a way of introducing new innovations to their club members. Both groups indicated that they used neighbors often as a source of information and therefore, crop production clubs members likely transfer information to others through this and other channels. They transfer technology through the adoption diffusion process as early adopters. From this study it can be concluded that crop production clubs do play a role in the technology transfer process

Compaction behavior of binary mixtures

Symposium on Powder Science and Technology - Powders and Sintered Material, Albi, FRANCE, MAY 23-25, 2007International audienceThe compaction behavior of binary mixtures of lactose and a functional excipient containing 98% of microcrystalline cellulose and 2% of silica was investigated by experiment. The densification process and the role of each component in the compaction behavior were examined by analyzing the effect of the composition on the stress transmission to the powder bed in axial (stress transmission) and in radial (stress transfer) directions. Unlike the behavior of a single component where the applied pressure is predominantly transmitted in the axial direction to the powder bed for densification, the increase of the composition of lactose up to 50% in mixtures increases the stress transfer that becomes greater than the stress transmission. However, for the compaction behavior of mixtures with 50% of lactose, two opposite behaviors were found, below and above a pressure around 70 MPa. Die-wall friction showed also a change at this pressure due to a smoothed contact surface with wall. By increasing the composition of lactose (>50%), the behavior of mixtures becomes dominated by the behavior of lactose where the transmission is better than the transfer. This study demonstrates that the analysis of the compaction behavior of mixtures by recording stress transmission, stress transfer and wall friction give pertinent information about the role of each component in the densification and Could be, to a certain extent, help to the selection of excipient for powder formulation

Reconstruction of the Social Capital-Based Agricultural Extension System in the Tengger Tribe Society in Tosari, Pasuruan, East Java, Indonesia

This study aims to examine the “how” and “what kind of” implementation process of extension by the needs of the Tengger Tribe in optimizing their social capital as an effort to accelerate the process of information and technology transfer to achieve the goals of extension that have been outlined in the philosophy of extension, namely behavior change farmers as an effort to improve welfare. This research useed a qualitative approach with a phenomenological method. Based on the research found that a system and implementation of extension were needed by local conditions, and accommodates tribe characteristics. The reconstruction of the extension system must be carried out thoroughly in terms of the institutional aspects of extension, extension workforce, and implementation of extension so that it could achieve the expected goals of changing farmer’s behavior to improve the welfare of farmers in the Tosari Sub-District of Pasuruan Regency

ANALISIS RESISTANCE FACTOR DALAM PENERAPAN PEMBELAJARAN BERBASIS ELEKTRONIK MENGGUNAKAN PENDEKATAN HUMAN-CENTERED-APPROACH

E-learning becomes an alternative way to transfer information effectively and efficiently in adopting information technology as a means of teaching and learning. Information technology applied must be Acceptable, if it’s not, it will display the behavior of resistance to change. This study uses the Human-Centered Approach-related resistance to change in preparation of the questionnaire instrument and using factor analysis in data processing and analysis. The process of taking samples using simple random sampling technique in which the taking of samples of the population that was randomly without regard to strata that exist in the population. Factor analysis model used is Principal Component Analysis (PCA). Phases of analysis of factors such as the correlation matrix, factor extraction, factor rotation, and interpretation of factors. Results from this research can be concluded that these factors play a role in the emergence of resistance to change in sequence from the most dominant factor Competence Factor, Motivation and Planning Implementation Factors, Communications in Leadership Factors, Culture Factor, Situations and Conditions Factors, Personality Factors, and Security Factor. It would be better if the sampling is not only for teachers but also involves students and mapped based on certain criteria which are equipped with the characteristics of each sample

Using Customer Segmentation to Build a Hybrid Recommendation Model

Camacho, P., de Almeida, A., & António, N. (2021). Using Customer Segmentation to Build a Hybrid Recommendation Model. In J. V. de Carvalho, P. Liberato, Á. Rocha, & A. Peña (Eds.), Advances in Tourism, Technology and Systems - Selected Papers from ICOTTS20 (pp. 299-308). (Smart Innovation, Systems and Technologies; Vol. 208). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-33-4256-9_27The growing trend in leisure tourism has been closely followed by the number of hospitality services. Nowadays, customers are more sophisticated and demand a personalized and simplified experience, which is commonly achieved through the use of technological means for anticipating customer behavior. Thus, the ability to predict a customer’s willingness to buy is also a growing trend in hospitality businesses to reach more customers and consolidate existing ones. The acquisition of a transfer service through website reservation generates data that can be used to perform customer segmentation and enable recommendations for other products or services to a customer, like recreation experiences. This work uses data from a Portuguese private transfer company to understand how its private transfer business customers can be segmented and how to predict their behavior to enhance services cross-selling. Information extracted from the data acquired with the private transfer reservations is used to train a model to predict customer willingness to buy, and based on it, offer leisure services to customers. For that, a hybrid classifier was trained to offer recommendations to a customer when he/she is booking a transfer. The model employs a two-phase process: first, a binary classifier asserts if the customer who’s buying the transfer would eventually buy a service experience. In that case, a multi-class model decides what should be the most likely experience to be recommended.authorsversionpublishe

Information transfer between stock market sectors: A comparison between the USA and China

Information diffusion within financial markets plays a crucial role in the process of price formation and the propagation of sentiment and risk. We perform a comparative analysis of information transfer between industry sectors of the Chinese and the USA stock markets, using daily sector indices for the period from 2000 to 2017. The information flow from one sector to another is measured by the transfer entropy of the daily returns of the two sector indices. We find that the most active sector in information exchange (i.e., the largest total information inflow and outflow) is the {\textit{non-bank financial}} sector in the Chinese market and the {\textit{technology}} sector in the USA market. This is consistent with the role of the non-bank sector in corporate financing in China and the impact of technological innovation in the USA. In each market, the most active sector is also the largest information sink that has the largest information inflow (i.e., inflow minus outflow). In contrast, we identify that the main information source is the {\textit{bank}} sector in the Chinese market and the {\textit{energy}} sector in the USA market. In the case of China, this is due to the importance of net bank lending as a signal of corporate activity and the role of energy pricing in affecting corporate profitability. There are sectors such as the {\textit{real estate}} sector that could be an information sink in one market but an information source in the other, showing the complex behavior of different markets. Overall, these findings show that stock markets are more synchronized, or ordered, during periods of turmoil than during periods of stability.Comment: 12 pages including 8 figure

A Framework for Assessing Knowledge Transfer Between Learners and Instructor Through Externalization Process

Knowledge transfer is important in the educational system. Most universities emphasize the effectiveness of knowledge transfer from the instructors to learners since the effectiveness of knowledge transfer can improve teaching methods. In the process of knowledge transfer from the instructors and learners, the three key characteristics of knowledge, knowledge ambiguity, knowledge disruption and knowledge distribution can cause problems in the knowledge transfer and thus affect the externalization of learners. This study is aimed in constructing a framework for assessing the knowledge transfer, by way of online learning, from the instructors to the learners and to examine the three key characteristics of knowledge and their relationship with the transfer process and the learning outcomes. The study used a mixed method design using the data collected from three universities in Southern Thailand. The data was analyzed using descriptive statistics and multiple regressions. The study too used the qualitative design for content analysis of the data collected from weblogs. The data was analyzed to determine the knowledge that learners gained and also the learners' reflection of the knowledge transfer. Using this analysis the effectiveness of online instructions from the instructors to learners was determined. The research findings revealed some significant results involving the three key characteristics of knowledge. The knowledge of learners was explained by 21.5 percent of knowledge ambiguity. In addition, 40.3 percent of perceived knowledge was explained by knowledge distribution. Finally, 41.3 percent was explained the learners' satisfaction when using tools and teaching techniques for knowledge distribution. The three key characteristics of knowledge together were, therefore, able to explain 64.3 percent of the learning outcomes, There are major important implications, for theory, as developed from this study: (1) A framework for assessing knowledge transfer can contribute much to the instructors and learners in knowing what knowledge that the instructors can transfer to learners and what knowledge is gained by the learners. This framework is useful for the instructors in their evaluation of knowledge transfer by learners. The knowledge can be transferred through online learning from the instructors to learners using methods and tools that are appropriate for knowledge transfer. (2) The knowledge gained is influenced by knowledge ambiguity. It is hoped that the instructor or instructors first of all find the appropriate methodology, in their efforts, to transfer knowledge to learners in the classroom and thus improve or make clear the knowledge before the transfer occurs. (3) A strong predictor of learners' behavior is knowledge disruption and as such it would be useful for the instructors to know the behavior of learners when using technology as a tool in transferring knowledge. (4) Another strong predictor for perceiving knowledge is knowledge distribution. The instructors need to know the prior knowledge of learners by testing the level of knowledge of the learners, whether it is low, medium or high before selecting the right methods to transfer knowledge. (5) Learners' satisfaction of tools and teaching techniques are also influenced by knowledge distribution. The instructors need to create information details which are suitable for the course. The study suggests that the instructors should allow learners time to study and use a program. In addition, the feedback of learners from weblogs do tell the instructors what the learners think of the knowledge transfer process, and what knowledge that can be externalized into documents from the process of knowledge transfer between the instructors and learners

Association Rules in Data Mining: An Application on a Clothing and Accessory Specialty Store

Retailers provide important functions that increase the value of the products and services they sell to consumers. Retailers value creating functions are providing assortment of products and services: breaking bulk, holding inventory, and providing services. For a long time, retail store managers have been interested in learning about within and cross-category purchase behavior of their customers, since valuable insights for designing marketing and/or targeted cross-selling programs can be derived. Especially, parallel to the development of information processing and communication technologies, it has become possible to transfer customers shopping information into databases with the help of barcode technology. Data mining is the technique presenting significant and useful information using of lots of data. Association rule mining is realized by using market basket analysis to discover relationships among items purchased by customers in transaction databases. In this study, association rules were estimated by using market basket analysis and taking support, confidence and lift measures into consideration. In the process of analysis, by using of data belonging to the year of 2012 from a clothing and accessory specialty store operating in the province of Osmaniye, a set of data related to 42.390 sales transactions including 9.000 different product kinds in 35 different product categories (SKU) were used. Analyses were carried out with the help of SPSS Clementine packet program and hence 25.470 rules were determined