Bridging the Business
Data Divide: Insights
into Primary and
Secondary Data Use by
Business Researchers
by Linda D. Lowry
ABSTRACT
Academic librarians and data specialists use a variety of approaches to gain insight into how researcher data needs and practices vary by discipline, including surveys, focus groups, and interviews. Some published studies included small numbers of business school faculty and graduate students in their samples, but provided little, if any, insight into variations within the business discipline. Business researchers employ a variety of research designs and data collection methods and engage in quantitative and qualitative data analysis. The purpose of this paper is to provide deeper insight into primary and secondary data use by business graduate students at one Canadian university based on a content analysis of a corpus of 32 Master of Science in Management theses. This paper explores variations in research designs and data collection methods between and within business subfields (e.g., accounting, finance, operations and information systems, marketing, or organization studies) in order to better understand the extent to which these researchers collect and analyze primary data or secondary data sources, including commercial or open data sources. The results of this analysis will inform the work of data specialists and liaison librarians who provide research data management services for business school researchers.
Keywords: business, primary data, secondary data,graduate students, research data management
LITERATURE REVIEW
Surveys and Interviews
Academic librarians and data specialists have used a variety of approaches to gain insight into current research data management practices such as case studies (e.g., Key Perspectives, 2010), campus-wide questionnaires (e.g., Parham, Bodnar & Fuchs, 2012), interviews (e.g., Carlson, 2012), and focus groups (e.g., McClure et al., 2014). One study revealed statistically significant differences in research data management practices and attitudes across four research domains (but did not consider discipline-specific distinctions), leading the authors to recommend tailoring data management services using discipline-specific approaches (Akers & Doty, 2013). Another study attempted to examine differences in research data practices by discipline and by methodology but the findings were of limited generalizability due to the low response rate and a survey instrument which confounded research strategies (e.g., qualitative, quantitative, and mixed methods) with research designs (e.g., experimental, survey, field work), and data collection methods (e.g., oral history, textual analysis) (Weller & Monroe-Gulick, 2014). Motivated by research funding agency requirements for data management plans, most studies have focused on the data curation behaviors and attitudes (such as data preservation and data sharing) of science researchers (e.g., Scaramozzino, Ramirez, & McGaughey, 2012), or if institution-wide, have grouped business scholars with social science or professional schools (e.g., Akers & Doty, 2013), thus providing little, if any, insight into variations within the business discipline. In the next section, I discuss how deeper insight into a researcher’s choice of data collection methods and patterns of secondary data use within a discipline can be acquired by conducting a content analysis of scholarly research publications such as journal articles, theses, and dissertations.
PURPOSE
The purpose of this study was to investigate the research designs and data collection methods of students in a research-based Master of Science in Management (MSCM) program in order to better understand the extent to which these researchers collected and analyzed primary or secondary data. A content analysis of a corpus of 32 master’s theses explored differences between and within subfields of business with respect to research designs and data collection methods. In cases where a thesis used secondary data, attempts were made to identify whether the data sources could be considered open data, or commercial data. This study explored the following research questions: 1 What is the distribution of theses by area of specialization and how does it compare to the distribution of core (supervisory) faculty? 2 What is the overall distribution of theses by research desig and by data collection method? What are the patterns of data collection method use within each type of research design? 3 What is the distribution of research designs and data collection methods by area of specialization? 4 What is the overall nature of primary and secondary data collection and use (across all specializations)? 5 What types of secondary sources are used in business research?
Do these researchers use open data sources, proprietary/commercial data sources, or both?
METHOD
In order to better understand the extent to which business student researchers collect and analyze primary or secondary data, I conducted a systematic content analysis of a corpus of 32 Master of Science in Management theses which were deposited in Brock University Library’s Digital Repository2. Master’s theses must be published in the digital repository as a graduation requirement, so this sample represented 100% of the MSCM degrees awarded since the inception of the program. Each thesis was hand coded using a hybrid approach of manifest and latent coding, similar to the approach taken by Nicholson and Bennett (2009), in order to identify the business subfield, research design, and data collection method employed, and the extent and nature of secondary data use (see Appendix A) . The full text of each thesis was reviewed, with particular attention paid to the title page, acknowledgements, abstract, table of contents, methods, and data sections.
SECONDARY SOURCES TYPES USED IN BUSINESS RESEARCH
This study investigated both the nature and types of secondary sources used and revealed that very few theses relied exclusively on open data sources. 28% of theses used commercial data sources exclusively, and 37% of theses used a combination of open and commercial data sources (see Table 5). Many theses used multiple secondary data sources, including four theses which used five or more secondary data sources (Table 5). A detailed listing of these open and commercial secondary data sources, including source type, example names, and frequency of use, is presented in Appendix D. The secondary sources included many of the data types identified in the Nicholson and Bennett (2009) study, but given this study’s Canadian location, it was not surprising to find some Canadian equivalents, such as SEDAR (for corporate financial reports and filings) and CANSIM (for socioeconomic data). Some, but not all, of the theses that used secondary sources relied on commercial numeric datasets hosted by the Library or Business School (e.g., Bloomberg Professional, CFMRC, Compustat, CRSP, Datastream). Other theses used datasets such as the Internet Retailer’s Top 500 Guide, which may have been purchased directly the student or provided by the student’s faculty advisor.
CONCLUSION
This study used the content analysis method to provide insight into primary and secondary data use by master’s level business students at one institution. The content analysis found variations in the choice of research designs and data collection methods use across the business discipline, as well as variations within business subfields. The results of this exploratory study can serve as a benchmark for future discipline-specific content analysis studies, and the content analysis method can be used to examine variations in data practices within other social science disciplines. The study could be extended to examine business research from multiple academic institutions, multiple career stages (e.g., doctoral students, faculty, and postdoctoral researchers), or a variety of types of research output including doctoral dissertations and peer-reviewed journal articles. The use of multiple coders would allow for the examination of a larger and more representative sample of the broader business research landscape. Given the Canadian Association of Research Libraries’ interest in developing a collaborative, networked approach to building a research data management infrastructure (for a discussion see Canadian Association of Research Libraries, 2013), a collaborative approach to conducting future discipline-specific content analysis studies is recommended.
NOTES
1 Linda D. Lowry is the business and economics liaison librarian at
Brock University in St. Catharines, Ontario, Canada. She can be
reached by email: llowry@brocku.ca
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In Indonesia
Jurnal Data Primer dan Sekunder pada Penelitian Bisnis
Pustakawan akademik dan spesialis data yang menggunakan berbagai pendekatan untuk mendapatkan wawasan tentang bagaimana data kebutuhan peneliti dan praktek bervariasi dengan disiplin, termasuk survei, kelompok fokus, dan wawancara. Beberapa penelitian yang diterbitkan termasuk sejumlah kecil dosen sekolah bisnis dan mahasiswa pascasarjana dalam sampel mereka, tetapi yang tersedia sedikit, jika ada, wawasan variasi dalam disiplin bisnis. peneliti bisnis menggunakan berbagai desain penelitian dan metode pengumpulan data dan terlibat dalam analisis data kuantitatif dan kualitatif. Tujuan dari makalah ini adalah untuk memberikan wawasan lebih dalam penggunaan data primer dan sekunder dengan mahasiswa pascasarjana bisnis di salah satu universitas Kanada didasarkan pada analisis isi dari korpus 32 Master of Science dalam tesis Manajemen. Makalah ini membahas variasi dalam desain penelitian dan metode pengumpulan data antara dan di dalam subbidang bisnis (misalnya, akuntansi, keuangan, operasi dan sistem informasi, pemasaran, atau studi organisasi) dalam rangka untuk lebih memahami sejauh mana peneliti mengumpulkan dan menganalisis data primer atau sumber data sekunder, termasuk sumber data komersial atau terbuka. Hasil analisis ini akan menginformasikan pekerjaan spesialis data dan pustakawan penghubung yang menyediakan layanan manajemen data penelitian bagi para peneliti sekolah bisnis.
JENIS DATA SEKUNDER YANG DIGUNAKAN DALAM PENELITIAN BISNIS
Studi ini meneliti kedua sifat dan jenis sumber sekunder yang digunakan dan mengungkapkan bahwa sangat sedikit tesis mengandalkan secara eksklusif pada sumber data yang terbuka. 28% dari tesis digunakan sumber data komersial eksklusif, dan 37% dari tesis menggunakan kombinasi sumber data yang terbuka dan komersial (lihat Tabel 5). Banyak tesis digunakan beberapa sumber data sekunder, termasuk empat tesis yang digunakan lima atau lebih sumber data sekunder (Tabel 5). Sebuah daftar rinci sumber-sumber data sekunder terbuka dan komersial, termasuk jenis sumber, misalnya nama, dan frekuensi penggunaan, disajikan dalam Lampiran D. sumber-sumber sekunder termasuk banyak dari jenis data yang diidentifikasi dalam Nicholson dan Bennett (2009) studi, tetapi mengingat lokasi Canadian studi ini, itu tidak mengherankan untuk menemukan beberapa setara Kanada, seperti SEDAR (untuk laporan keuangan perusahaan dan pengajuan) dan CANSIM (untuk data sosial ekonomi). Beberapa, tetapi tidak semua, dari tesis yang menggunakan sumber sekunder mengandalkan dataset numerik komersial diselenggarakan oleh Perpustakaan atau Business School (mis, Bloomberg Professional, CFMRC, Compustat, CRSP, Datastream). Tesis lain yang digunakan dataset seperti Internet Pengecer Top 500 Panduan, yang mungkin telah dibeli langsung siswa atau disediakan oleh penasihat fakultas siswa.
KESIMPULAN
Penelitian ini menggunakan metode analisis isi untuk memberikan wawasan digunakan data primer dan sekunder dengan mahasiswa bisnis tingkat master di salah satu institusi. Analisis isi menemukan variasi dalam pilihan desain penelitian dan metode pengumpulan data menggunakan seluruh disiplin bisnis, serta variasi dalam subbidang bisnis. Hasil studi eksplorasi ini dapat berfungsi sebagai patokan untuk studi analisis isi disiplin khusus masa depan, dan metode analisis isi dapat digunakan untuk memeriksa variasi dalam praktek data dalam disiplin ilmu sosial lainnya. Studi ini bisa diperpanjang untuk memeriksa riset bisnis dari lembaga akademis beberapa, beberapa tahapan karir (misalnya, mahasiswa doktoral, fakultas, dan peneliti postdoctoral), atau berbagai jenis hasil penelitian termasuk disertasi doktor dan peer-review artikel jurnal. Penggunaan beberapa coders akan memungkinkan untuk pemeriksaan sampel yang lebih besar dan lebih representatif dari lanskap penelitian bisnis yang lebih luas. Mengingat Asosiasi Kanada kepentingan Penelitian Perpustakaan 'dalam mengembangkan kolaboratif, pendekatan jaringan untuk membangun infrastruktur manajemen data penelitian (untuk diskusi melihat Canadian Association of Research Libraries, 2013), pendekatan kolaboratif untuk melakukan studi analisis isi disiplin khusus masa depan direkomendasikan.
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