Wyniki wyszukiwania - BazTech

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Do the innovation and digital transformation strategies induce SME performances in new normal era? Structural & confirmatory analysis models

Elsaman Hosam Azat, Tamadher Aldabbagh, Said Dina Sabry, Kousihan Suriya Kumaran, Japos Genaro V.

Acta Innovations

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2023

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no. 47

41--55

EN

One of major challenge in a sustainable growth, which organizations face is a slow adoption of the digital transformation. This research work presents the reasons that lead to the slow digitization process in medical device SMEs in southern Germany. In addition, by developing the conceptual model, this work highlights the effect of these improper implementations on SME's business performances and financial situation. The researchers applied correlational research design methodology, with simple random sampling techniques along with empirical and statistical study with primary data collection. The main study variables are SME’s financial situation, SMEs organizational performance, and medical digitization rules. The study demonstrated the negative impact of delayed digital mechanisms in terms of businesses and financial performances.The extra transparency restrictions that add burdens for SMEs, and the lack of training for the employees, which in overall add more difficulties for adopting innovation and digital transformation are other factors negatively affecting the studied process.

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Application of factor analysis in company management — selected examples related to competitiveness and market success

Jurczak Jolanta, Jurczak Grzegorz

Engineering Management in Production and Services

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2021

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Vol. 13, no. 3

25--36

EN

Factor analysis is a standard statistical technique for reducing data dimensionality, which is widely used in sociology, psychology, and demography. Also, financial and insurance institutions commonly use such a technique for marketing research. In recent years, factor analysis has been used, at the beginning rather diffidently, to analyse selected problems of business management, e.g. to troubleshoot consumer and company communication. There are some literature reports about the successful use of factor analysis in managing a company area. Nevertheless, the literature seems to lack examples with successful use of the method with a clear explanation of its rather difficult application in the field of competitiveness or potential company boost. The modest popularity of such a powerful technique in this particular field seems to be attributed mainly to the complexity of the method and its requirements concerning the data quantity. Besides, the factor analysis technique has great potential and can be used as an efficient tool to reduce the complexity of observed phenomenon or verify the accuracy of theoretical models. Therefore, the purpose of this paper is to present a vast potential of factor analysis (both exploratory and confirmatory) applied to solve various problems in company management, especially related to competitiveness and market success. Two case studies covering the subject of business management are presented to illustrate the benefits of factor analysis application. The exploratory factor analysis is exemplified by the search of factors related to the commercial success of the company, while the confirmatory technique is illustrated by a case study of the intellectual capital of the company and its factors related to competitiveness. The paper also presents the essence of the factor analysis, types of analysis, subsequent procedures, purposes, and its specific features. Finally, the applicability of the factor analysis to solve management issues and possible gain in management are discussed.

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Prioritization of barriers to lean implementation in Indian automotive small & medium sized enterprises

Tiwari R. K., Tiwari J. K.

Management and Production Engineering Review

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2018

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Vol. 9, No. 2

69--79

EN

Lean manufacturing has been the most deliberated concept ever since its introduction. Many organization across the world implemented lean concept and witnessed dramatic improvements in all contemporary performance parameters. Lean manufacturing has been a sort of mirage for the Indian automotive industry. The present research investigated the key lean barriers to lean implementation through literature survey, confirmatory factor analysis, multiple regression, and analytic network process. The general factors to lean implementation were inadequate lean planning, resource constraints, half-hearted commitment from management, and behavioral issues. The most important factor in the context of lean implementation in Indian automotive industry was inadequate lean planning found with the help of confirmatory factor analysis and multiple regression analysis. Further analysis of these extracted factors through analytic network process suggested the key lean barriers in Indian automotive industry, starting from the most important were absence of proper lean implementation methodology, lack of customer focus, absence of proper lean measurement system, inadequate capital, improper selection of lean tools & practices, leadership issues, resistance to change, and poorly defined roles & responsibilities. Though literature identifying various lean barriers are available. The novelty of current research emerges from the identification and subsequent prioritization of key lean barriers within Indian automotive SMEs environment. The research assists in smooth transition from traditional to lean system by identifying key barriers and developing customized framework of lean implementation for Indian automotive SMEs.

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Workplace innovation: exploratory and confirmatory factor analysis for construct validation

Wipulanusat W., Panuwatwanich K., Stewart R. A.

Management and Production Engineering Review

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2017

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Vol. 8, No. 2

57--68

EN

Workplace innovation enables the development and improvement of products, processes and services leading simultaneously to improvement in organisational performance. This study has the purpose of examining the factor structure of workplace innovation. Survey data, extracted from the 2014 APS employee census, comprising 3,125 engineering professionals in the Commonwealth of Australia’s departments were analysed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). EFA returned a two-factor structure explaining 69.1% of the variance of the construct. CFA revealed that a two-factor structure was indicated as a validated model (GFI = 0.98, AGFI = 0.95, RMSEA = 0.08, RMR = 0.02, IFI = 0.98, NFI = 0.98, CFI = 0.98, and TLI = 0.96). Both factors showed good reliability of the scale (Individual creativity: α = 0.83, CR = 0.86, and AVE = 0.62; Team Innovation: α = 0.82, CR = 0.88, and AVE = 0.61). These results confirm that the two factors extracted for characterising workplace innovation included individual creativity and team innovation.

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Wybrane metody statystyki wielowymiarowej w zastosowaniu do badań technicznego wyposażenia gospodarstw

Dąbkowski J., Roczkowska-Chmaj S.

Problemy Inżynierii Rolniczej

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2001

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R. 9, nr 1

69-82

PL

W obszernym wprowadzeniu do zasadniczych wyników tej parcy przedstawiono dostępne wspołcześnie metody statystyki, przeznaczone do analizowania złóżonych struktur danych wielowymiarowych. Omawiane metody stanowią rozwinięcie klasycznych procedur, takich jak analiza wariancji, analiza czynnikowa, analiza tabel wielodzielczych, itp. Ogólnie rzecz ujmując pozwalają one na redukcję wymiarów analizowanej przestrzeni cech, bądź na zdejmowanie powiązań między cechami, z możliwością uwzględnienia wielkości niedostępnych bezpośrednio w pomiarach, a odzwierciedlających strukturę badanego systemu rzeczywistego. Procedury te są dostępne w postaci opcji lub modułów w większości komercyjnych pakietów statystycznych i praca niniejsza ma na celu między innymi ich spopularyzowanie w środowisku inżynierii rolniczej. Zastosowanie jednej z opisywanych metod (tzw. analizy równań strukturalnych zilustrowano na przykładzie danych opisujących techniczną infrastrukturę 112 gospodarstw indywidualnych regionu Polski Południowej. Praca jest kontynuacją badań nad różnymi metodami analizy wielowymiarowej przestrzeni cech opisujących techniczne wyposażenie gospodarstw. Uzyskane wyniki wskazują, że można tworzyć efektywne modele strukturalne badanych populacji, pozwalające na uproszczenie opisu oraz ułatwienie klasyfikacji złożonych struktur danych dotyczących technicznej infrastruktury.

EN

An extensive introduction to results of this study presents recently available statistical methods designed to analyse the complex structure of multidimensional data. Discussed methods comprise the expansion of classical procedure, such as variance analysis, factor analysis, contigency table analysis etc. Generally, they enable to reduce the dimensions of analysed features' extent, or to find out the features' interrelations with the possibility of including the quantities that are inaccessible directly by measurements but reflect the structure of real system. The procedures, in form of options or moduli, are available in majority of commercial statistical packets; this work makes an attempt to popularize them in the environment of agricultural engineering. The application of one from among described methods, i.e. the structural equation analysis, was illustrated on an example of data describing technical infrastructure of 112 family farms in region of the southern Poland. Obtained results indicate the possibility of developing effective structural models of studied populations that enable to simplify the description and to make easier the classification of complex data structure dealing with the technical infrastructure of the farms.