Factors of successful innovation in services and a performance comparison with manufacturing sector

Ropret, Marko; Fatur, Peter; Rodman, Karmen; Likar, Borut

doi:10.1504/ijil.2012.049351

Cited by 11 publications

(6 citation statements)

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“…office buildings, lands and properties, and machines and equipments) when evaluating a firm's market value and brand. The term intellectual capital (IC) has emerged as top executives recognize the contributions from human capital, customer knowledge, process knowledge, technical expertise, experiences, and supplier and customer relations (Chen et al , 2005; Ropret et al , 2012).…”

Section: Introductionmentioning

confidence: 99%

Productivity management: integrating the intellectual capital

Phusavat

Comepa

Sitko-Lutek

et al. 2013

Industrial Management &Amp; Data Systems

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PurposeThe intangible assets are important today as knowledge and innovation are the key drivers to long‐term business competitiveness. In other words, this competitiveness requires the productive use of the intangible assets. Thus, measuring productivity should underline their importance within an organization. Therefore, the study aims to examine whether the intellectual capital or IC can be used to support productivity measurement.Design/methodology/approachThe research methodology consists of two stages, derived from the management process which deals with measurement and analysis. The first stage tests the interrelationships between productivity (namely value‐added labor productivity) and the IC. This test is based on a company's financial reports and the IC survey. The second stage focuses on better understanding on how IC can be analyzed. Altogether ten leading manufacturers, with 270 executives and managers, have participated in the survey. Important statistical techniques such as Pearson Correlation are integrated. Moreover, the consideration into the validity of the survey items (e.g. the non‐respondent bias analysis) is illustrated.FindingsBecause of the significant relationships between the IC and value‐added productivity, measuring the IC can strengthen ongoing productivity measurement efforts on a firm's intangible assets. In other words, the IC can become a surrogate for productivity measurement. To assist the IC analysis further, the IC is positively influenced by innovation, learning organization, knowledge management, and self‐directed learning, respectively. In other words, the innovation appears to have the highest impact on the IC level while the ability of an organization to learn and to apply knowledge also has considerable influences.Originality/valueThe emerging use of the term value‐added highlights the importance of IC within the context of productivity measurement. Past studies have focused on relating some the IC components such as innovation and quality of work life to the productivity level. This study attempts to look at the IC in a more comprehensive manner.

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Section: Introductionmentioning

confidence: 99%

Productivity management: integrating the intellectual capital

Phusavat

Comepa

Sitko-Lutek

et al. 2013

Industrial Management &Amp; Data Systems

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“…As observed by Hjalager (2010), tourism entities often declare themselves to be innovative merely on the basis of identified new customers and strengthening brands, which she understands to be a misuse of the term "innovation". Innovation actually depends on managing several other factors, such as R&D expenditure, information K 43,3/4 and communication technology, knowledge management processes, culture, organizational structure, management systems and the process of assets allocation (Biloslavo, 2005;Fatur and Likar, 2009;Ropret et al, 2012). Moreover, even among the innovation factors, correlations can exist (Fatur and Likar, 2009).…”

Section: Discussionmentioning

confidence: 99%

The systems approach to the improvement of innovation in Slovenian tourism

2014

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Purpose -This paper aims to analyse whether and how the Development Plan and Policies of Slovenian Tourism (SiPlan) could be improved systematically and systemically, enabling more comprehensive management of innovation. Design/methodology/approach -The data were obtained within a comprehensive national innovation study. Data analysis was performed in four phases. In the initial phase, a link between the innovation project and SiPlan was established. In the next phase, which of the innovation factors are significantly correlated with the tourism destination development concept was identified. In the third phase, further policy potential for improving the innovation factors was identified. In the last phase, a systems approach was applied to develop a qualitative systems model, a causal loop diagram, taking into consideration the empirically identified strengths and weaknesses of the current SiPlan and other pertinent factors. Findings -The results of empirical research indicate that SiPlan represents a valuable, but not optimum development model of Slovene tourism development. Therefore, the authors propose a qualitative tourism development model based on the research results and a systems dynamics methodology. Originality/value -The work is important from the scientific point of view, i.e. as a methodology and research results that could be applied in further research activities. In addition, the results could be usefully used by policy makers by way of focusing on the most influential factors: policies that have a potential for the systems (holistic) and socially responsible development of tourism in Slovenia.

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“…The underlying mathematics is comparable, to that of regression analysis, and the choice of which type of test to use is based on study design, not on the advantages of one or other technique (Kemp & Kemp, 2004). If we are interested evaluating several aspects of the data (e.g., strength of relationship, variance explained) secondary to the overall significance, regression analysis is recommendable (Kemp & Kemp, 2004, Ropret et al, 2012. As the ANOVA method tests the hypotheses of differences between within-group conditions, but does not determine which groups are different from the other, pairwise comparisons were done using a Bonferroni post-hoc test.…”

Section: Methodsmentioning

confidence: 99%

The Perception of Administrative Barriers and Their Implications for SMEs’ Performance: Evidence from Slovenia

Ropret

Aristovnik

Ravšelj

2018

Zagreb International Review of Economics and Business

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The importance of small and medium-sized enterprises (SMEs) is widely recognised for the Slovenian economy. However, the issues regarding legislative and other administrative barriers and their perception by SMEs as a heterogeneous group of enterprises are not yet fully investigated. The main research hypothesis concerns that there exist significant differences in the perception of administrative barriers among characteristic SME groups. Consequently, this paper aims to provide a comprehensive analysis of the key administrative barriers SMEs face in Slovenia. This entails three activities: (1) identifying the main areas in which barriers are found; (2) establishing what they imply performance-wise; and (3) providing policymaker guidelines tailored to different SME groups (size, legal form, sector, age). The empirical results, based on one-way analysis of variance (ANOVA) and Bonferroni post hoc tests on a sample of 925 SMEs, show differences in the various groups of SMEs mentioned above. Thus, it is shown that it is most promising to address the administrative barriers through an in-depth approach that targets specific enterprise groups and is reflected within guidelines for responsible policymakers.

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Factors of successful innovation in services and a performance comparison with manufacturing sector

Cited by 11 publications

References 0 publications

Productivity management: integrating the intellectual capital

Productivity management: integrating the intellectual capital

The systems approach to the improvement of innovation in Slovenian tourism

The Perception of Administrative Barriers and Their Implications for SMEs’ Performance: Evidence from Slovenia

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