Dynamic capabilities : axiomatic formation of firms’ competitive competencies

The capabilities concept is critical in understanding the competitive competencies of firms. Capabilities allow firms to sense, seize and reconfigure their resources in response to opportunities and threats within their environments. This systematic review reviewed a total of 37 Scopus database-selected peer-reviewed articles on capabilities, technology, innovation, and capability frameworks. The purpose was to identify and discuss firms’ capabilities and formation processes and effects on competitive advantages to generate an encompassing framework that overcomes the limited and fragmented nature of current capability frameworks. The study employed thematic content analysis and author-anchored keywords analysis which enabled the identification of several themes regarding capabilities and formation processes. The findings of the study were discussed under the following themes: technological capabilities; supply chain capabilities; networking, collaboration, interactive, coordinating, and alignment capabilities; organisational capabilities; and lastly systems capabilities. The study contributes to enlightening a body of firms’ capabilities theories and generated an encompassing interactive capabilities framework to guide researchers in understanding firms’ capabilities formation processes. The value of the study to the research community lies in emphasising the multi-level approach (macro; mezzo; firm level) and the virtues of combining tenets from different frameworks for a nuanced understanding of firms’ capabilities development. The study will be critical in guiding firms in building their capabilities, particularly the importance of open innovation networks and collaboration in reducing innovation risks and costs. The paper is important to policy makers regarding the institutions facilitating the interaction of international, national and firms level dynamics in propping and propelling firms’ capabilities development.The Department of Research and Innovation (University of Pretoria) and York Timbers - South Africa.https://www.sciencedirect.com/journal/social-sciences-and-humanities-openam2024Graduate School of Technology Management (GSTM)SDG-09: Industry, innovation and infrastructur

Developing a model to evaluate the impacts of science, technology and innovation foresight on policy-making

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Strategies Small Business Owners Use to Remain Sustainable

In the United States, 41% of small retail businesses fail to succeed for longer than 5 years. The purpose of this multiple case study was to explore strategies small retail business owners used to remain sustainable for more than 5 years. The conceptual framework that grounded this study was Schumpeter\u27s innovation theory. The sample size of this research included 4 successful retail business owners located in the southeastern region of the United States who have successfully started and managed their business activities for more than 5 years. Data were collected using semistructured face-to-face interviews with successful owners of small retail businesses and reviews of the organizations\u27 internal documents. Data were coded, categorized, and labeled using coding techniques, and then validated using member checking. Data analysis processes included a thematic analysis method to identify emerging themes. The results of data analysis revealed 3 significant themes: passion and determination for doing business, market development and customer satisfaction, and business model innovation. The results indicated that the use of innovation theory enabled small retail business owners to develop innovative strategies to sustain the business for more than 5 years. The results also showed that innovation increases sales and profits for the longer term. The implications of this study for positive social change include the potential to create new jobs, enhance tax revenues and growth for governments, and improve social environments from revenue generated by employment

Exploring Strategies for Measuring Team Innovation in Small Financial Business

Small financial business leaders cannot maintain a competitive advantage without effectively measuring work team innovation. The purpose of this qualitative exploratory multiple case study was to explore the strategies that small financial business leaders use to measure work team innovation to maintain a competitive advantage. The conceptual framework undergirding this study was Schumpeter’s innovation management theory. The research question asked what strategies small financial business leaders use to effectively measure work team innovation to maintain a competitive advantage. Interview data were collected from 15 small financial business leaders who employ less than 100 employees in Madison, Chester, Gibson, Henderson, and Crockett counties in west Tennessee and are members of a local Chamber of Commerce. Data analysis used descriptive coding method. The findings showed that small financial business leaders understand the importance of using innovation appropriately in their organization to maximize organizational performance on the work team level. Small financial business leaders acknowledged the effect COVID-19 had on the work environment and that the focus of their organization should be on the customers’ needs over the needs of their organization. This study’s positive social change implications could be that small financial businesses that use innovation appropriately in their organization might increase customer satisfaction and increase organizational success

Data-driven Technology Foresight: Text Analysis of Emerging Technologies

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 산업·조선공학부, 2018. 2. 박용태.This dissertation argues for new directions in the field of technology foresight. Technology foresight was formulated on the basis of qualitative and participatory research. Initially, most foresight activities were triggered by the prospect of a handful number of experts, but recent studies highlight theoretical paradigm shifts toward a more comprehensive and data-driven approach to creating shared insights on the future of emerging technologies. Much of the research up to now, however, has been descriptive in nature, and a definite method of realizing the notion has not yet been addressed in the existing literature to a large extent. To this end, we have attempted to formalize the concept of data-driven technology foresight by incorporating unconventional data sources – future-oriented web data, Wikipedia data, and scientific publication data – and different analytical tools – Latent Semantic Analysis, IdeaGraph, and Morphological Analysis. Four distinct foresight frameworks were proposed for the proactive management process of emerging technologies: impact identification, impact analysis, plan development, and technology ideation. The study was guided by the following research questions: (1) what kinds of data sources are available on the web and which of those are considered useful in foresight studies? (2) Where could we incorporate these data sources and which techniques are most suitable for the given purposes? (3) Which foresight-related fields would particularly benefit from applying a data-driven approach and what are the positive effects? The proposals outlined should be considered exploratory and open-ended. It is designed to determine the nature of the problem, rather than to offer definitive and conclusive answers. Nevertheless, the proposed scheme may well provide not just a rationale but a theoretical grounding for this newly introduced notion. This dissertation is expected to yield a foothold for the readers to better comprehend and act on this new shift in the field of technology foresight.Chapter 1 Introduction 1 1.1 Emergence of Technology Foresight 1 1.2 Towards a Data-driven Technology Foresight 3 1.3 Problem Statement 6 1.4 Dissertation Overview 8 Chapter 2 Data Sources and Methodologies 15 2.1 Data Sources 15 2.1.1 Future-oriented Web Data 15 2.1.2 Wikipedia Data 17 2.1.3 Scientific Publication Data 19 2.2 Methodologies 21 2.2.1 Latent Semantic Analysis (LSA) 21 2.2.2 IdeaGraph 25 2.2.3 Morphological Analysis (MA) 29 Chapter 3 Foresight for Impact Identification 31 3.1 Introduction 32 3.2 Emerging Technology and its Social Impacts 36 3.2.1 Distinctive Nature of Emerging Technology 36 3.2.2 Technology Assessment 39 3.3 LSA for Constructing Scenarios 43 3.4 Research Framework 44 3.4.1 Step 1: Data Collection 46 3.4.2 Step 2: Scenario Development 49 3.4.2.1 Pre-LSA: Preprocessing Future-oriented Web Data 49 3.4.2.2 LSA: Applying Latent Semantic Analysis 52 3.4.2.3 Post-LSA: Constructing Scenarios 54 3.5 Illustrative Case Study: Drone Technology 55 3.6 Discussion 65 3.6.1 Categorization of Social Impacts 65 3.6.2 Comparative Analysis 72 3.6.3 Implication for Theory, Practice, and Policy 74 3.7 Conclusion 76 Chapter 4 Foresight for Impact Analysis 79 4.1 Introduction 80 4.2 Uncertainty and Complexity 82 4.3 Data-driven Foresight Process 84 4.4 Scenario Building Beyond the Obvious 86 4.4.1 Capturing Plausibility using LSA 90 4.4.2 Capturing Creativity using IdeaGraph 92 4.5 Research Framework 93 4.5.1 Step 1. Pre-Analysis: Data Preparation 94 4.5.1.1 Target Technology Selection 94 4.5.1.2 Data Acquisition 95 4.5.1.3 Data Preprocessing 95 4.5.2 Step 2. Text Analysis: Scenario Building 96 4.5.2.1 General Glimpse using Overt Structures 96 4.5.2.2 Hidden Details using Latent Structures 98 4.5.3 Step 3. Post-Analysis: Analytical Interpretation 101 4.5.3.1 Individual Impact Scenario 101 4.5.3.2 Overall Latent Impacts 101 4.6 Illustrative Case Study: 3D Printing Technology 102 4.7 Discussion 110 4.7.1 Scenarios Beyond the Obvious 110 4.7.2 Comparative Analysis 113 4.8 Conclusion 115 Chapter 5 Foresight for Plan Development 117 5.1 Introduction 118 5.2 Theoretical Paradigm Shift 120 5.2.1 Technology-focused vs. Society-focused 120 5.2.2 Co-evolution of Technology and Society 122 5.2.3 Responsible Development 125 5.3 Methodological Paradigm Shift 127 5.3.1 Participatory Approach 127 5.3.2 Data-driven Approach 129 5.4 Rationale for using LSA 131 5.5 Research Framework 132 5.5.1 Step 1. Envisioning Social Issues 133 5.5.1.1 Collection of Future-oriented Web Data 133 5.5.1.2 Construction of Impact Scenarios 135 5.5.1.3 Conceptualization of Impact Scenarios 137 5.5.2 Step 2. Deriving Technical Solutions 138 5.5.2.1 Collection of Scientific Publication Data 138 5.5.2.2 Construction of Solution Concepts 139 5.6 Illustrative Case Study: Autonomous Vehicle 140 5.7 Discussion 149 5.7.1 Comparative Analysis 149 5.7.2 Major Strengths in Envisioning Social Impacts 152 5.7.3 Major Strengths in Overviewing Solutions 154 5.8 Conclusion 156 Chapter 6 Foresight for Technology Ideation 158 6.1 Introduction 159 6.2 Related Studies 161 6.2.1 Generating Creative Ideas 161 6.2.2 Data-driven Morphological Analysis 163 6.3 Technology Foresight using Wikipedia 165 6.3.1 Wikipedia as a Good Remedy 165 6.3.2 Preliminaries: How to Apply Wikipedia 168 6.4 Research Framework 173 6.4.1 Basic Model 174 6.4.2 Extended Model 175 6.4.2.1 Phase 1: Preliminary Phase 177 6.4.2.2 Phase 2: Dimension Development Phase 177 6.4.2.3 Phase 3: Value Development Phase 179 6.4.2.4 Phase 4: Sub-dimension Development Phase 182 6.5 Illustrative Case Study: Drone Technology 183 6.5.1 Basic Model 183 6.5.2 Extended Model 185 6.6 Comparative Analysis 193 6.6.1 Experimental Setup 193 6.6.2 Comparison of Results 195 6.7 Intrinsic Limitations of Applying Wikipedia 199 6.8 Conclusion 201 Chapter 7 Concluding Remarks 203 Bibliography 211 Appendix 236 Appendix A Result of overt and latent structures of each impact scenario 236 Appendix B Result of Wikipedia-based morphological matrix (basic model) 240 Appendix C Result of Wikipedia-based morphological matrix using superordinate seed terms (extended model) 241 Appendix D Result of Wikipedia-based morphological matrix after applying subordinate value seed terms (extended model) 243 Appendix E Result of Wikipedia-based morphological matrix after developing sub-dimensions (extended model) 247Docto