TTO characteristics and university entrepreneurship: a cluster analysis

2019 ◽  
Vol 10 (4) ◽  
pp. 861-889 ◽  
Author(s):  
Mariluz Fernandez-Alles ◽  
Juan Pablo Diánez-González ◽  
Tamara Rodríguez-González ◽  
Mercedes Villanueva-Flores
Keyword(s):  
Cluster Analysis ◽  
Efficient Design ◽  
Content Type ◽  
University Entrepreneurship ◽  
Multivariate Technique ◽  
Hierarchical Agglomerative Cluster ◽  
Technology Transfer Offices ◽  
Design Characteristics ◽  
The Relationship ◽  
Hierarchical Agglomerative Cluster Analysis

Purpose The purpose of this paper is to analyze potentially significant differences in a series of relevant characteristics of universities’ technology transfer offices (TTOs). To this end, TTOs have been classified by the function of their resources assigned to the enhancement of university entrepreneurship. The factors analyzed are the number of academic spin-offs created with the support of TTOs as well as the TTOs’ age, experience, professionalization and relational capital. Design/methodology/approach The authors have performed a hierarchical agglomerative cluster analysis to identify the groups of TTOs with homogeneous behavior and features. This multivariate technique allows determining whether it is possible to identify some differentiated conglomerates of TTOs. Findings The results of the cluster analysis allow concluding that the number of academic spin-offs created with the support of TTOs, the age and degree of professionalization of these TTOs, the experiences of their employees in matters related to entrepreneurship and their relationships with market actors explain the different levels of commitment of TTOs toward the enhancement of university entrepreneurship. In contrast with the expected results, the relationship between TTOs and academic actors does not seem to explain such differences. Originality/value This research contributes to the identification of the particular design characteristics that TTOs should exhibit to promote the entrepreneurial performance of universities, offering important recommendations to academic institutions regarding the efficient design of TTOs to manage university ambidexterity and to build TTOs’ entrepreneurial identity.

Strategic orientations, knowledge management (KM) and business performance

Kybernetes ◽  
2019 ◽  
Vol 48 (9) ◽  
pp. 1942-1964 ◽  
Author(s):  
Mona Jami Pour ◽  
Mohammad Asarian
Keyword(s):  
Cluster Analysis ◽  
Knowledge Management ◽  
Business Performance ◽  
High Performance ◽  
Strategic Orientation ◽  
Content Type ◽  
Strategic Orientations ◽  
Strategy Performance ◽  
High Level ◽  
The Relationship

Purpose Despite the huge amount of studies that have investigated the strategy–performance relationships and knowledge management (KM)–performance relationships, there is little consensus regarding the nature of these connections. By reviewing related literature, some notable limitations and inconsistent results are highlighted in extant studies. To address these challenges, this study aims to explore the effects of strategic orientation and KM mechanisms on business performance. Design/methodology/approach The study conducted an empirical investigation of 227 small- and medium-sized enterprises (SMEs) to explore the relationship between strategy−performance and KM−performance. Business strategy is conceptualized as a comparative construct with six dimensions, KM is conceptualized by two types of KM mechanisms of technical and non-technical KM mechanisms and business performance is measured by four dimensions of balanced scorecard (BSC). The cluster analysis was used to explore different aspects of these three constructs. Findings Using cluster analysis, the results indicate that firms with high level of analysis, defensiveness, futurity and proactiveness in strategic orientation have better performance and also the high level of both KM mechanisms another important finding shows that firms with more KM mechanisms have high performance and technical mechanisms have more predictor role on performance. Practical implications This research also has prescriptive implications for strategic managers and KM practitioners. The finding enhanced the understanding of the relationship between strategic orientations, KM and performance. The results assist managers to assess business performance regarding strategic orientations and KM mechanisms of the firms. Therefore, it helps firms to improve strategic resource allocation and exploit KM investment by considering ideal pattern of the performance. Originality/value By reviewing strategic management and KM literature, it is revealed that there are little studies about how the interaction of strategic orientation and KM influences business performance. The main contribution of the study is exploring the profile of the firms by considering their strategic orientation and KM mechanisms and their impact on business performance. This study provides an empirical evidence about interaction of strategic orientations, KM mechanisms and business performance in SME context, which is merely investigated in previous researches.

On the polysemy of the Polish complete path construction: A corpus-based exploratory study

2019 ◽  
Vol 55 (4) ◽  
pp. 631-670
Author(s):  
Daria Bębeniec ◽  
Małgorzata Cudna
Keyword(s):  
Cluster Analysis ◽  
Random Sample ◽  
Exploratory Study ◽  
Semantic Features ◽  
Hierarchical Agglomerative Cluster ◽  
Usage Patterns ◽  
Complete Path ◽  
Hierarchical Agglomerative Cluster Analysis ◽  
National Corpus

Abstract In this article, we present a corpus-based analysis of two major types of the Polish Complete Path (CP) construction in which a source-PP, headed by od+GEN, is immediately followed by a goal-PP, headed by do+GEN or po+ACC, as in od jesieni 1920 do jesieni 1921 ‘from autumn 1920 to autumn 1921’ and od kreskówek po rysunki techniczne ‘from cartoons to technical drawings’. The aim of the study is to shed some light on the polysemous structure of the CP construction on the basis of its usage patterns. To this end, we used a random sample of over 500 instances of both construction types retrieved from the National Corpus of Polish. The data were annotated for a number formal and semantic features and subsequently explored using hierarchical agglomerative cluster analysis. When interpreting the results of several analyses performed on different sets of variables, we gave special attention to three levels of semantic granularity encoded in the data, concluding that, on the whole, all analyses point towards a distinction between the spatial, temporal and abstract meanings of the construction under investigation.

Towards a classification of supply chain relationships: a routine based perspective

2017 ◽  
Vol 22 (4) ◽  
pp. 341-374 ◽  
Author(s):  
Muhammad Usman Ahmed ◽  
Mehmet Murat Kristal ◽  
Mark Pagell ◽  
Thomas F. Gattiker
Keyword(s):  
Cluster Analysis ◽  
Supply Chain ◽  
Design Methodology ◽  
Measurement Properties ◽  
Supplier Relationships ◽  
Content Type ◽  
Supply Chain Relationships ◽  
Research Questions ◽  
The Relationship

Purpose This paper studies buyer–supplier relationships (BSRs) by taking a routine-based approach and develops a taxonomy of BSRs. Recent advances in the BSR literature have shown that firms implement a host of diverse routines, called integrative practices, with their supply chain partners. Relationships differ based on what integrative practices are present in them. This paper aims to develop a taxonomy of supply chain relationships based on integrative practices measured at the relationship level. Design/methodology/approach The authors use survey data collected from North American manufacturers to establish the measurement properties of new relationship level constructs that represent different aspects of integration. Cluster analysis is used with these new constructs to develop a taxonomy of supply chain relationships. Regression and bootstrapping techniques are used to establish the predictive validity and stability of the taxonomy. Findings The results show four distinct types of relationships. On comparison, the authors find salient differences between their results and past classifications. As a result of taking a routine-based multidimensional view of integration, the authors find two types of relationships that have not been discovered by past taxonomies. Originality/value The new relationship level constructs will allow academics to have greater precision in their research questions on BSRs, as not all aspects of integration behave in the same manner. The four types of relationships identified by this study provide a useful framework to manage supply chain relationships for practitioners.

Developing a motivation-based segmentation typology of Facebook users

2015 ◽  
Vol 33 (7) ◽  
pp. 1071-1086 ◽  
Author(s):  
Wei Shao ◽  
Mitchell Ross ◽  
Debra Grace
Keyword(s):  
Cluster Analysis ◽  
Information Seeking ◽  
Hierarchical Cluster ◽  
Demographic Variables ◽  
Cluster Solution ◽  
Full Spectrum ◽  
Content Type ◽  
Segmentation Strategy ◽  
The Relationship ◽  
User Motivation

Purpose – The purpose of this paper is to demonstrate the importance of user-motivation as well as demographics in developing an effective segmentation strategy of Facebook users. Additionally, the paper seeks to add validity to the scale developed by Park et al. (2009) by using a full spectrum of Facebook users. Design/methodology/approach – A self-administered survey was employed to explore access motivations, frequency and session duration of Facebook users. The survey was e-mailed to 2,129 potential respondents with 530 valid responses received. Data were initially analysed by hierarchical cluster analysis to develop the cluster solution. Cluster means were then used as cluster centres for a K-means cluster analysis for all cases. The relationship between the clusters and Facebook activity variables was investigated through ANOVA while independent samples t-tests were employed to analyse the relationship between motivations and demographics. Lastly χ2-tests were used to explore the relationship between Facebook user segments and demographics. Findings – The results indicate four distinct types of Facebook users: Devotee, Agnostic, Socializer and Finder. Devotees were highly positive about Facebook use while Agnostics were least motivated to use Facebook. Socializers were motivated to use Facebook for socializing and entertainment while Finders were motivated to use Facebook for information seeking. These four distinct groups are validated by examining their individual behaviour regarding frequency of access to Facebook and the average amount of time spent on Facebook per visit. Demographic variables such as gender and age were found to be significantly related to Facebook user-motivation and segmentation. Practical implications – For marketers who communicate with market segments via social media, the findings of this study are highly significant. To date, marketers have found it difficult to fully exploit the benefits of Facebook. The authors argue this is due to a tendency to consider Facebook users as a single segment rather than understanding the nuances of different user segments. This research provides marketers with a motivation and demographic segmentation strategy for Facebook users. Originality/value – Despite the popularity of Facebook as a communication channel, from a marketing perspective little is known regarding Facebook user segments. This research addresses this gap by undertaking a segmentation study of Facebook users. A segmentation typology is developed in which both Facebook user motivations as well as demographic variables are found to be useful in describing user segments. Additionally, the study makes important theoretical contributions by extending uses and gratifications theory to the Facebook context and adding validity to the scale developed by Park et al. (2009) for use with the full spectrum of Facebook users.

scholarly journals Cluster Analysis of Haze Episodes Based on Topological Features

2020 ◽  
Vol 12 (10) ◽  
pp. 3985
Author(s):  
Nur Fariha Syaqina Zulkepli ◽  
Mohd Salmi Md Noorani ◽  
Fatimah Abdul Razak ◽  
Munira Ismail ◽  
Mohd Almie Alias
Keyword(s):  
Cluster Analysis ◽  
Persistent Homology ◽  
Topological Data Analysis ◽  
Data Sets ◽  
Air Quality Monitoring ◽  
Hierarchical Agglomerative Cluster ◽  
Topological Features ◽  
Hidden Patterns ◽  
Air Quality Monitoring Stations ◽  
Hierarchical Agglomerative Cluster Analysis

Severe haze episodes have periodically occurred in Southeast Asia, specifically taunting Malaysia with adverse effects. A technique called cluster analysis was used to analyze these occurrences. Traditional cluster analysis, in particular, hierarchical agglomerative cluster analysis (HACA), was applied directly to data sets. The data sets may contain hidden patterns that can be explored. In this paper, this underlying information was captured via persistent homology, a topological data analysis (TDA) tool, which extracts topological features including components, holes, and cavities in the data sets. In particular, an improved version of HACA was proposed by combining HACA and persistent homology. Additionally, a comparative study between traditional HACA and improved HACA was done using particulate matter data, which was the major pollutant found during haze episodes by the Klang, Petaling Jaya, and Shah Alam air quality monitoring stations. The effectiveness of these two clustering approaches was evaluated based on their ability to cluster the months according to the haze condition. The results showed that clustering based on topological features via the improved HACA approach was able to correctly group the months with severe haze compared to clustering them without such features, and these results were consistent for all three locations.

scholarly journals Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

2015 ◽  
Vol 8 (11) ◽  
pp. 4979-4991 ◽  
Author(s):  
I. Crawford ◽  
S. Ruske ◽  
D. O. Topping ◽  
M. W. Gallagher
Keyword(s):  
Cluster Analysis ◽  
Asymmetry Factor ◽  
Z Score ◽  
Desktop Computer ◽  
Data Set ◽  
Hierarchical Agglomerative Cluster ◽  
Bacterial Aerosol ◽  
Ambient Data ◽  
Spectrometer Data ◽  
Hierarchical Agglomerative Cluster Analysis

Abstract. In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs) by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio–hydro–atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen–Rocky Mountain Biogenic Aerosol Study) ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misattribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed, yielding an explicit cluster attribution for each particle and improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

Inter-organizational fit and environmental innovation in supply chains

2018 ◽  
Vol 38 (8) ◽  
pp. 1683-1704 ◽  
Author(s):  
Yongyi Shou ◽  
Wen Che ◽  
Jing Dai ◽  
Fu Jia
Keyword(s):  
Cluster Analysis ◽  
Supply Chain ◽  
Supply Chains ◽  
Design Methodology ◽  
Canonical Discriminant Analysis ◽  
Environmental Innovation ◽  
Organizational Fit ◽  
Content Type ◽  
Cluster Membership ◽  
The Relationship

Purpose Through examining the two constructs of inter-organizational complementarity and inter-organizational compatibility in supply chains, the purpose of this paper is to develop a taxonomy of focal firms’ inter-organizational fit (IOF) configurations with their suppliers and customers, and examine the relationship between these configurations and environmental innovation (EI) in order to answer the question of “with whom” to collaborate for EI development. Design/methodology/approach A survey instrument was elaborated and data from a sample of 171 US firms were collected. The authors adopted cluster analysis to identify the IOF taxonomy. Canonical discriminant analysis was employed to uncover underlying dimensions between clustering variables and cluster membership. Then, ANOVA tests were conducted to investigate relationships between IOF configurations in the context of EI in supply chains. Findings Three configurations were identified based on the complementarity and compatibility between focal firms and their supply chain partners. It is observed that the overall IOF level is positively related to firms’ EI outcomes. Moreover, inter-organizational complementarity facilitates incremental EI while inter-organizational compatibility plays a more crucial role in radical EI. Both are required to achieve the best innovation outcome. Originality/value This research develops the first taxonomy for depicting IOF in a supply chain innovation context and also clarifies different rationale behind the development of incremental and radical EI through examining distinctive effects of the complementarity and compatibility with supply chain partners.

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