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The fourth industrial revolution (i.e., Industry 4.0), marked by cyber-physical systems, interconnected supply network, automated and autonomous processes, decentralized decision making, is enabled (and enables) big data. Notwithstanding our ever-growing understanding of how big data can technically be managed, our business and societal understanding of how value can be created and captured with big data has remained at an embryonic stage. As such, the existing body of knowledge is dispersed and implicit on how big data-enabled business models can be developed and implemented, how value creation and appropriation can be orchestrated in network settings, how big data value creation can be explained from the existing organizational theories, and how big data driven transition of firms can be monitored and evaluated.
This PhD research aims to address the foregoing interrelated gaps and contribute to the extant business model theories and emerging scholarly discourse on the business value of big data. Equally important is the practical implication of the proposed research that centers on how firms can ensure value creation and appropriation in their big data transformation.
Tasks
The PhD candidate will conduct the following tasks during his/her four-year appointment:
The applicant must fulfill the following requirements:
In addition to the requirements included above, potential PhD candidates may have certain skills, experiences or abilities that are not required, but are considered to be an advantage:
Fixed-term contract: 18 months with possible extension to 4 years.
The PhD project is a salaried position, on a full-time basis, which means that the appointed PhD candidate is employee (promovendus) of Nyenrode Business University. Salary and benefits are in accordance with the collective labor agreement. In addition, a holiday allowance, end-of-year bonus, and a generous number of vacation days are part of employment conditions. The accepted candidate is appointed on a full-time basis for a duration up to four years, starting with a 18 month appointment. The PhD position is intended to start 1 February 2020.
Nyenrode Business University is one of the most prominently present business universities in the Dutch business market with a strong European outreach. The contemporary technologies and technological trends with impact on business market is therefore of essential interest for the university. In this regard, the growing interest and adoption of big data in the past few years cannot go unheeded. While the technical side of big data is often the focus on many technical universities, Nyenrode Business University and its corporate partners can benefit from insights into business values of big data and big data driven business models.
Nyenrode is a small-scale private university, positioned among the top European business schools, founded in 1946 for and by business, with an international orientation. Nyenrode offers a broad range of degree and executive education programs in business, management, accountancy and controlling, and conducts research in these disciplines. The mission of Nyenrode is: ‘Serving society by shaping responsible leaders’.
Center of Principal Supervisor
Center for Marketing & Supply Chain Management
Nyenrode PhD School
The appointed PhD candidate will enroll in Nyenrode’s PhD program. The PhD program at Nyenrode offers a number of courses at beginner, intermediate and advanced PhD level. The PhD school hosts a yearly PhD conference and organizes several social events for its PhD students each year. As part of his or her enrollment in this program, the PhD candidate must successfully complete several mandatory courses and workshops including but not limited to ‘philosophy of science’, ‘academic writing skills’, ‘research data management’ and ‘scientific integrity’. In addition, the appointed PhD candidate will need to successfully complete three research electives.
Within three months after one’s appointment, the PhD candidate will, in consultation with one’s PhD supervisor/supervisory team, complete and submit a training and supervision plan. Yearly progress talks with the principal supervisor/supervisory team will take place and progress forms documenting progress and goals will be submitted to the PhD school.
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