Survey dataset of Dynamic Capabilities for leading and managing Digital Transformation initiatives
Description
The dataset presented in this article originates from a study aimed at developing a Dynamic Capabilities (DC) framework for managing Digital Transformation (DT) initiatives in organizations, integrating Change Management (CM). The data were collected using a mixed-methods approach, which included qualitative expert interviews and two quantitative surveys. The two surveys that were conducted: Expert Survey and Mass Survey. The first (Expert Survey) consisted of 130 questions and included responses from 31 DT experts, assessing their expertise in DT and the importance, difficulty, and extent performed of DC (Sensing , Seizing, and Transforming) routine activities. The second survey (Mass Survey) consisted of 38 questions and comprised 446 responses from professionals across fifty-one countries and various industries; it evaluated the framework’s applicability in real-world organizational contexts. The Mass Survey included the DT challenges, organizational culture profiles, dynamic capabilities, and demographic details such as level of focus and organization size. Both surveys asked participants to rate their level of DT success and specify their organisation’s industry type. The data from both surveys are structured into categorical and Likert scale responses. The dataset can be used for further analysis, including comparative studies of DT strategies across sectors or regions, and for developing tools for managing DT. Additionally, it holds potential for reuse in training and educational materials for managers and practitioners overseeing DT projects. The Excel sheet has four tabs: (1) Variables Expert Survey, (2) Expert Survey Data, (3) Variable Mass Survey, and (4) Mass Survey Data. The Variable tabs (1 and 3) provide the variables that were used in the Expert and Mass Surveys respectively. The Data sheets (2 and 4) are the raw datasets that were collected from participants.
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To compile the dataset, the framework for Dynamic Capabilities and Change Management in Digital Transformation was developed based on a thorough review of existing literature (Albino, 2021; Annarelli et al., 2021; Berbel-Vera et al., 2022; Cannas, 2021; Chirumalla, 2021; Colli et al., 2022; Day and Schoemaker, 2016; Ellström et al., 2022; Fellenstein and Umaganthan, 2019; Hsu et al., 2018; Khurana et al., 2022; Linde et al., 2021; Matarazzo et al., 2021; Warner and Wäger, 2019; Witschel et al., 2019; Yu et al., 2022). The framework was then validated through a series of expert reviewers and survey studies. The initial framework was derived from key literature on Dynamic Capabilities, Change Management, and Digital Transformation. The framework was designed to integrate these concepts into a cohesive model organisations could use to effectively manage Digital Transformation initiatives. To ensure the framework's validity and comprehensiveness, it underwent validation by five experts in the fields of Digital Transformation and Change Management. The validation process followed Rabionet's semi-structured interview methodology (Rabionet, 2011), which involved in-depth interviews with these experts to gather their insights and feedback on the framework. The interview process was designed to capture detailed qualitative data, which was then analysed; the feedback from experts improved and validated the Dynamic Capabilities framework that was developed and surveyed. The survey instrument was formulated based on the validated framework. The survey aimed to assess the applicability and effectiveness of the framework across various organisational contexts. Both the Expert and Mass surveys used the Taherdoost (2016) method for sampling, the process is as follows: (1) clearly define target population, (2) select sampling frame, (3) choose sampling technique, (4) determine sample size, (5) collect data, and (6) assess response rate. Survey Monkey was the tool used to conduct the survey. The survey design process was iterative, ensuring that the survey was comprehensive, clear, and covered all essential inquiries. The steps followed to create the survey were the following: 1. Develop survey using the refined framework 2. Conduct initial survey validation 3. Make necessary adjustments 4. Complete submission for ethical clearance 5. Make necessary adjustments 6. Pilot test survey with a small group 7. Make necessary adjustments 8. Send out survey Survey responses were analysed using Statistica software. The analysis included descriptive statistics, reliability analysis (Cronbach’s alpha), and regression analysis to evaluate the framework's applicability and the relationships between different variables. A professional statistician validated the statistical analysis and interpretation of findings to ensure the accuracy and reliability of the results.