Role of Digital Platforms in Entrepreneurial Processes: A Resource Enabling Perspective of Startups in Pakistan

• URL: http://arxiv.org/abs/2108.09943v1
• Date: Mon, 23 Aug 2021 05:30:26 GMT
• Title: Role of Digital Platforms in Entrepreneurial Processes: A Resource Enabling Perspective of Startups in Pakistan
• Authors: Hareem Nassar and Fareesa Malik
• Abstract summary: The recent infusion of digital platforms into different aspects of innovation and entrepreneurship has supported digital entrepreneurship. This study focuses on digital platform-based startups of Pakistan and draws on entrepreneurial bricolage theory to understand the enabling external resources.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: This article aims to explore the role of digital platforms as external enablers in entrepreneurial processes. The recent infusion of digital platforms into different aspects of innovation and entrepreneurship has supported digital entrepreneurship; however, the altered entrepreneurial processes are yet to be explored. This study focuses on digital platform-based startups of Pakistan and draws on entrepreneurial bricolage theory to understand the enabling external resources. We followed multiple qualitative case studies approach and collected data through semi-structured interviews from two startups operating solely on digital platforms, 1) XYLEXA and 2) Toycycle. The findings show that entrepreneurial process is a continuous process. Digital platforms have made entrepreneurial processes less bounded i.e. the products and services keep on evolving even after they have been endorsed to the end user. Moreover, platform-based startups having limited resources can move through the entire entrepreneurial process by combining available resources efficiently and effectively.

Related papers

• Empowering Real-World: A Survey on the Technology, Practice, and Evaluation of LLM-driven Industry Agents [63.03252293761656]
  This paper systematically reviews the technologies, applications, and evaluation methods of industry agents based on large language models (LLMs)<n>We examine the three key technological pillars that support the advancement of agent capabilities: Memory, Planning, and Tool Use.<n>We provide an overview of the application of industry agents in real-world domains such as digital engineering, scientific discovery, embodied intelligence, collaborative business execution, and complex system simulation.
  arXiv  Detail & Related papers  (2025-10-20T12:46:55Z)
• A Cooperative Approach for Knowledge-based Business Process Design in a Public Authority [0.0]
  This paper presents a knowledge-based method to support business experts in designing business processes.<n>The construction of the knowledge base starts from simple, text-based, knowledge artefacts and then progresses towards more structured, formal representations.
  arXiv  Detail & Related papers  (2025-07-26T07:31:28Z)
• From Web Search towards Agentic Deep Research: Incentivizing Search with Reasoning Agents [96.65646344634524]
  Large Language Models (LLMs), endowed with reasoning and agentic capabilities, are ushering in a new paradigm termed Agentic Deep Research.<n>We trace the evolution from static web search to interactive, agent-based systems that plan, explore, and learn.<n>We demonstrate that Agentic Deep Research not only significantly outperforms existing approaches, but is also poised to become the dominant paradigm for future information seeking.
  arXiv  Detail & Related papers  (2025-06-23T17:27:19Z)
• Pivoting B2B platform business models: From platform experimentation to multi-platform integration to ecosystem envelopment [1.124958340749622]
  Digital servitization in the manufacturing sector is evolving, marked by a strategic shift from traditional product-centric to platform business models (BMs) This article advances B2B platform BMs and digital servitization literature, highlighting the efficacy of a progressive approach and strategic pivoting.
  arXiv  Detail & Related papers  (2024-12-27T21:34:05Z)
• Empowering Cognitive Digital Twins with Generative Foundation Models: Developing a Low-Carbon Integrated Freight Transportation System [6.87702244676681]
  We develop digital twins for real-time awareness, predictive analytics, and urban logistics optimization. Recent advancements in generative AI offer new opportunities to streamline digital twins. We propose a conceptual framework employing transformer-based language models to enhance an urban digital twin.
  arXiv  Detail & Related papers  (2024-10-08T05:53:20Z)
• Digital Twins of Business Processes: A Research Manifesto [1.773489607375694]
  The Internet of Things has heavily been adopted in organizational and industrial settings to monitor and automatize physical processes. Advanced ways of managing and maintaining business processes come within reach as there is a Digital Twin of a business process. This manifesto paper aims to contribute to the current state of the art by clarifying the relationship between business processes and Digital Twins.
  arXiv  Detail & Related papers  (2024-09-25T15:43:46Z)
• A Fused Large Language Model for Predicting Startup Success [21.75303916815358]
  We develop a machine learning approach with the aim of locating successful startups on venture capital platforms. Specifically, we develop, train, and evaluate a tailored, fused large language model to predict startup success. Using 20,172 online profiles from Crunchbase, we find that our fused large language model can predict startup success.
  arXiv  Detail & Related papers  (2024-09-05T16:22:31Z)
• Digital Business Model Analysis Using a Large Language Model [1.5500145658862499]
  This study proposes an LLM-based method for comparing and analyzing similar companies from different business do-mains. This method can support idea generation in digital business model design.
  arXiv  Detail & Related papers  (2024-06-09T11:16:11Z)
• From Digital Twins to Digital Twin Prototypes: Concepts, Formalization, and Applications [55.57032418885258]
  There is no consensual definition of what a digital twin is. Our digital twin prototype (DTP) approach supports engineers during the development and automated testing of embedded software systems.
  arXiv  Detail & Related papers  (2024-01-15T22:13:48Z)
• A digital business ecosystem maturity model for personal service firms [0.0]
  As of today, personal service firms lack the know-how and experience on how to implement processes and practices to build digital business ecosystems. We propose a maturity model, which offers guidance for this sector to be able to achieve the transition from analog to digital.
  arXiv  Detail & Related papers  (2022-11-02T13:25:43Z)
• YMIR: A Rapid Data-centric Development Platform for Vision Applications [82.67319997259622]
  This paper introduces an open source platform for rapid development of computer vision applications. The platform puts the efficient data development at the center of the machine learning development process.
  arXiv  Detail & Related papers  (2021-11-19T05:02:55Z)
• X-modaler: A Versatile and High-performance Codebase for Cross-modal Analytics [99.03895740754402]
  X-modaler encapsulates the state-of-the-art cross-modal analytics into several general-purpose stages. X-modaler is an Apache-licensed, and its source codes, sample projects and pre-trained models are available on-line.
  arXiv  Detail & Related papers  (2021-08-18T16:05:30Z)
• OSOUM Framework for Trading Data Research [79.0383470835073]
  We supply, to the best of our knowledge, the first open source simulation platform, Open SOUrce Market Simulator (OSOUM) to analyze trading markets and specifically data markets. We describe and implement a specific data market model, consisting of two types of agents: sellers who own various datasets available for acquisition, and buyers searching for relevant and beneficial datasets for purchase. Although commercial frameworks, intended for handling data markets, already exist, we provide a free and extensive end-to-end research tool for simulating possible behavior for both buyers and sellers participating in (data) markets.
  arXiv  Detail & Related papers  (2021-02-18T09:20:26Z)
• SoMin.ai: Personality-Driven Content Generation Platform [60.49416044866648]
  We showcase the World's first personality-driven marketing content generation platform, called SoMin.ai. The platform combines deep multi-view personality profiling framework and style generative adversarial networks. It can be used for the enhancement of the social networking user experience as well as for content marketing routines.
  arXiv  Detail & Related papers  (2020-11-30T08:33:39Z)
• Knowledge Integration of Collaborative Product Design Using Cloud Computing Infrastructure [65.2157099438235]
  The main focus of this paper is the concept of ongoing research in providing the knowledge integration service for collaborative product design and development using cloud computing infrastructure. Proposed knowledge integration services support users by giving real-time access to knowledge resources.
  arXiv  Detail & Related papers  (2020-01-16T18:44:27Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.