Knowledge-Based Service (KBS) Opportunities to Contour Startup Into a Scalable Enterprise

2021 ◽  
pp. 238-247
Author(s):  
Deepak Yadav ◽  
Niladari Das ◽  
Paritosh Tripathi
Keyword(s):  
Early Stage ◽  
Research Work ◽  
New Venture ◽  
Knowledge Based ◽  
Venture Investment ◽  
Assessment Validation ◽  
National Economic ◽  
Growing Economy ◽  
Research And Education ◽  
Founding Team

The essential transition step from a startup to a sustainable organization in early-stage entrepreneurs is very crucial. The four stages in the life cycle of an entrepreneurial venture consists of ideation, transition, scaling-up, and growth/exit and is efficiently done by knowledge-based services (KBS). The founding team faced the key challenges which emphasize assessment, validation, and enhancement of the business concept. KBS is a large and fast-growing economy based on businesses and professions which lays a concrete foundation to build a scalable business. KBS are highly recommended opportunities for new venture investment and growth and have created more than 79% out of all nonfarm US jobs. This area has been paid very little attention to entrepreneurship research and education which hampers national economic expansion. This article discusses entrepreneurship education, research and investment in KBS. KBS research work explores exclusive features, opportunities, and challenges in new venture development to a scalable enterprise.

Knowledge-Based Service (KBS) Opportunities to Contour Startup Into a Scalable Enterprise

2020 ◽  
Vol 5 (1) ◽  
pp. 56-64
Author(s):  
Deepak Yadav ◽  
Niladari Das ◽  
Paritosh Tripathi
Keyword(s):  
Early Stage ◽  
Research Work ◽  
New Venture ◽  
Knowledge Based ◽  
Venture Investment ◽  
Assessment Validation ◽  
National Economic ◽  
Growing Economy ◽  
Research And Education ◽  
Founding Team

The essential transition step from a startup to a sustainable organization in early-stage entrepreneurs is very crucial. The four stages in the life cycle of an entrepreneurial venture consists of ideation, transition, scaling-up, and growth/exit and is efficiently done by knowledge-based services (KBS). The founding team faced the key challenges which emphasize assessment, validation, and enhancement of the business concept. KBS is a large and fast-growing economy based on businesses and professions which lays a concrete foundation to build a scalable business. KBS are highly recommended opportunities for new venture investment and growth and have created more than 79% out of all nonfarm US jobs. This area has been paid very little attention to entrepreneurship research and education which hampers national economic expansion. This article discusses entrepreneurship education, research and investment in KBS. KBS research work explores exclusive features, opportunities, and challenges in new venture development to a scalable enterprise.

What Do We Know About New Venture Investment Time Patterns?

2018 ◽  
Vol 21 (01) ◽  
pp. 1850004
Author(s):  
Reinhard Schulte
Keyword(s):  
New Venture ◽  
Future Research ◽  
New Firms ◽  
Business Decisions ◽  
Time Pattern ◽  
Knowledge Based ◽  
Body Of Knowledge ◽  
Venture Investment ◽  
Time Patterns ◽  
New Firm

This paper contributes to the literature on new firms in two ways. First, by addressing new venture investment, it focusses on a largely neglected, but important, issue of new firm business decisions. Secondly, it provides a valuable picture for how investing by new businesses is going to evolve over time. Our results suggest that investments by new firms are prone to an s-shaped time pattern rather than a random, linear, or a gradually growing trajectory or a capital market-driven behavior as is assumed usually in the literature on investment decisions. By constructing a framework for future research on new venture investment, this article suggests specific research opportunities for future contributions to this body of knowledge. Based on the developed theorem, four main strands for future research can be identified, namely, (1) the empirical validation of the theorem per se, including trajectory, duration, and level of investment; (2) the link between investment and funding of the venture; (3) the link between investment and new venture development; and (4) investment as an adjustment of aggregate capital stock.

scholarly journals Knowledge-based Lean Six Sigma maintenance system for sustainable buildings

2017 ◽  
Vol 8 (1) ◽  
pp. 109-130 ◽  
Author(s):  
Jasim Aldairi ◽  
M.K. Khan ◽  
J. Eduardo Munive-Hernandez
Keyword(s):  
Conceptual Framework ◽  
Six Sigma ◽  
Research Work ◽  
Lean Six Sigma ◽  
Rule Base ◽  
Sustainable Buildings ◽  
Sustainable Building ◽  
Content Type ◽  
Environmentally Sustainable ◽  
Knowledge Based

Purpose This paper aims to develop a knowledge-based (KB) system for Lean Six Sigma (LSS) maintenance in environmentally sustainable buildings (Lean6-SBM). Design/methodology/approach The Lean6-SBM conceptual framework has been developed using the rule base approach of KB system and joint integration with gauge absence prerequisites (GAP) technique. A comprehensive literature review is given for the main pillars of the framework with a typical output of GAP analysis. Findings Implementation of LSS in the sustainable building maintenance context requires a pre-assessment of the organisation’s capabilities. A conceptual framework with a design structure is proposed to tackle this issue with the provision of an enhancing strategic and operational decision-making hierarchy. Research limitations/implications Future research work might consider validating this framework in other type of industries. Practical implications Maintenance activities in environmentally sustainable buildings must take prodigious standards into consideration, and, therefore, a robust quality assurance measure has to be integrated. Originality/value The significance of this research is to present a novel use of hybrid KB/GAP methodologies to develop a Lean6-SBM system. The originality and novelty of this approach will assist in identifying quality perspectives while implementing different maintenance strategies in the sustainable building context.

scholarly journals Evolution of Semantic Similarity—A Survey

2021 ◽  
Vol 54 (2) ◽  
pp. 1-37
Author(s):  
Dhivya Chandrasekaran ◽  
Vijay Mago
Keyword(s):  
Natural Language ◽  
Semantic Similarity ◽  
Language Processing ◽  
Hybrid Methods ◽  
Research Work ◽  
Similarity Measures ◽  
Text Data ◽  
Knowledge Based ◽  
Open Research ◽  
Research Problems

Estimating the semantic similarity between text data is one of the challenging and open research problems in the field of Natural Language Processing (NLP). The versatility of natural language makes it difficult to define rule-based methods for determining semantic similarity measures. To address this issue, various semantic similarity methods have been proposed over the years. This survey article traces the evolution of such methods beginning from traditional NLP techniques such as kernel-based methods to the most recent research work on transformer-based models, categorizing them based on their underlying principles as knowledge-based, corpus-based, deep neural network–based methods, and hybrid methods. Discussing the strengths and weaknesses of each method, this survey provides a comprehensive view of existing systems in place for new researchers to experiment and develop innovative ideas to address the issue of semantic similarity.

Automated monitoring and assessment of productivity in earthmoving projects

2018 ◽  
Vol 45 (11) ◽  
pp. 958-972 ◽  
Author(s):  
Ashraf Salem ◽  
Osama Moselhi
Keyword(s):  
Data Fusion ◽  
Continuous Monitoring ◽  
Research Work ◽  
Sensor Data ◽  
Fusion Algorithm ◽  
Cost Overruns ◽  
Knowledge Based ◽  
Monitoring Model ◽  
Multi Sensor Data Fusion ◽  
Proposed Model

Continuous monitoring of productivity and assessment of its variations are crucial processes that significantly contribute to success of earthmoving projects. Numerous factors may lead to productivity variations. However, these factors are subjectively identified using manual knowledge-based expert judgment. Such manual recognition process is not only subject to errors but also time-consuming. There is a lack of research work that focuses on near real-time assessment of productivity variation and its effect on cost, schedule and effective utilization of resources in earthmoving projects. This paper presents a customized multi-source automated data acquisition model that acquires data from a variety of wireless sensing technologies. The acquired multi-sensor data are transmitted to a central MySQL database. Then a newly developed data fusion algorithm is applied for truck state recognition, and hence the duration of each earthmoving state. Multi-sensor data fusion facilitates measurement of actual productivity, and consequently the assessment of productivity ratios that support continuous monitoring of productivity variation in earthmoving operations. The developed tracking and monitoring model generates an early warning that supports proactive decisions to avoid schedule delays, cost overruns, and inefficient depletion of resources. A case study is used to reveal the applicability of the proposed model in monitoring and assessing actual productivity and its deviations from planned productivity. Finally, results are discussed and conclusions are drawn highlighting the features of the proposed model.

Early stage network engagement strategies in the network capability development of new ventures

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Helen McGrath ◽  
Thomas O'Toole
Keyword(s):  
Social Network ◽  
Business Strategy ◽  
Early Stage ◽  
New Ventures ◽  
New Venture ◽  
Capability Development ◽  
Content Type ◽  
Study Approach ◽  
Engagement Strategies ◽  
Network Capability

Purpose The purpose of this paper is to identify the early stage network engagement strategies that new ventures use to gain traction in interaction in the development of network capability. Design/methodology/approach Using 24 new ventures in the micro-brewing industry in Ireland, Belgium and the USA as an empirical base, the authors use an inductive case study approach owing to the exploratory nature of the research aim and the lack of prior literature in the area. Findings The findings suggest five early stage network engagement process strategies in network capability development: business-to-business network prospecting; co-branding/co-promoting activities; from maker-mindset to adapting; social media platforming; and recognition and activation of network role. Research limitations/implications The findings are limited to the micro-brewery sector at one point in time, although in multiple country contexts. Analyzing other sectors and taking a temporal view of strategizing, analyzing the sector at another time point, would show how dynamics in engagement change as the actors acquire new experiences from interaction. Practical implications The potential to gain from network resources and the paucity of these resources in new ventures makes early stage engagement strategizing for network capability development an attractive business strategy for new firms. All firms are born within a social network that has economic importance. Identifying the five early stage network engagement strategies can mitigate the challenge for the new venture in moving from the initial social network to collaborating within wider business networks to gain access to resources, technology and customers. Originality/value Strategizing in new venture contexts is a relatively new stream of research for the industrial marketing and purchasing group. This paper adds to the growing body of literature that places interaction, relationships and networks at the heart of strategy making and provides important insights for new ventures, which may lead to earlier and greater success for the firms. The authors respond to calls for increased research addressing capability development in a new venture context and for research to take a more interactive perspective on new venture processes.

Linking Key Performance Indicators to New International Venture Survival

2016 ◽  
Vol 15 (3) ◽  
pp. 31-48
Author(s):  
Yasheng Chen ◽  
Johnny Jermias
Keyword(s):  
Life Cycle ◽  
Performance Measures ◽  
Early Stage ◽  
Bankruptcy Prediction ◽  
New Venture ◽  
Business Success ◽  
Employee Productivity ◽  
Financial Measures ◽  
Start Up ◽  
Financial Performance Measures

ABSTRACT Based on the four major challenges firms face in the early stage of their life cycle, we identify and use financial and non-financial performance measures to predict the survivability of new international ventures. We use a sample of 3,729 new manufacturing ventures from the Chinese Foreign Invested Enterprises Database. The study sample consists of wholly owned ventures of multi-national corporations (MNCs) and joint ventures between pairs comprising foreign and local investors in China. The results are consistent with the study's hypotheses. Using the Cox (1972) survival model, we find that employee training, employee productivity, accounts receivable collection period, export intensity, and sales growth are positively related to new venture survival. This study contributes to the existing business venturing and accounting literature in three ways. First, it fills the gap in the existing literature on bankruptcy prediction by focusing on firms in the early stage of their life cycle. Second, it uses survivability as a measure of business success. Survivability is a more comprehensive measure of firm performance than traditional financial measures during the start-up stage because during this stage firms tend to carry large losses that make financial measures inappropriate. Finally, this study has the potential to help new venture managers improve a firm's chances of success by using customized performance measures that fit its unique situation. JEL Classifications: D21; G32; M41.

Personal Knowledge Management by the Knowledge Citizen

2010 ◽  
pp. 131-140
Author(s):  
América Martínez Sánchez
Keyword(s):  
Knowledge Management ◽  
Building Block ◽  
Research Work ◽  
Individual Performance ◽  
Individual Development ◽  
Personal Knowledge ◽  
Strong Impact ◽  
Personal Knowledge Management ◽  
Knowledge Based ◽  
The Individual

The discipline of Personal Knowledge Management (PKM) is depicted in this chapter as a dimension that has been implicitly present within the scope and evolution of the Knowledge Management (KM) movement. Moreover, it is recognized as the dimension that brought forth Knowledge-based Development (KBD) schemes at organizational and societal levels. Hence, this piece of research work aims to develop parallel paths between Knowledge Management moments and generations and the PKM movement. KM will be depicted as a reference framework for a state-of-the-art review of PKM. A number of PKM authors and models are identified and categorized within the KM key moments and generations according to their characteristics and core statements. Moreover, this chapter shows a glimpse of the knowledge citizen’s PKM as an aspect with strong impact on his/her competencies profile; which in turn drives his/her influence and value-adding capacity within knowledge-based schemes at organizational and societal levels. In this sense, the competencies profile of the knowledge citizen is of essence. Competencies are understood as the individual performance of the knowledge citizen interacting with others in a given value context. The chapter concludes with some considerations on the individual development that enables PKM to become a key element in the knowledge citizen’s profile, such as the building block or living cell that triggers Knowledge-based Development at organizational and societal levels.

Analytical Model for High–Level Area Estimation of FPGA Design

2016 ◽  
Vol 7 (2) ◽  
pp. 35-44
Author(s):  
Rachna Singh ◽  
Arvind Rajawat
Keyword(s):  
Early Stage ◽  
Estimation Error ◽  
Research Work ◽  
Performance Estimation ◽  
Estimation Accuracy ◽  
Accurate Estimation ◽  
Fpga Design ◽  
Estimation Model ◽  
Area Estimation ◽  
High Level

FPGAs have been used as a target platform because they have increasingly interesting in system design and due to the rapid technological progress ever larger devices are commercially affordable. These trends make FPGAs an alternative in application areas where extensive data processing plays an important role. Consequently, the desire emerges for early performance estimation in order to quantify the FPGA approach. A mathematical model has been presented that estimates the maximum number of LUTs consumed by the hardware synthesized for different FPGAs using LLVM.. The motivation behind this research work is to design an area modeling approach for FPGA based implementation at an early stage of design. The equation based area estimation model permits immediate and accurate estimation of resources. Two important criteria used to judge the quality of the results were estimation accuracy and runtime. Experimental results show that estimation error is in the range of 1.33% to 7.26% for Spartan 3E, 1.6% to 5.63% for Virtex-2pro and 2.3% to 6.02% for Virtex-5.

scholarly journals Creating New Ventures: A Review and Research Agenda

2020 ◽  
Vol 47 (1) ◽  
pp. 11-42 ◽  
Author(s):  
Dean A. Shepherd ◽  
Vangelis Souitaris ◽  
Marc Gruber
Keyword(s):  
Organizational Behavior ◽  
Social Relationships ◽  
Research Agenda ◽  
New Ventures ◽  
New Venture ◽  
Future Research ◽  
The Past ◽  
Road Map ◽  
Organizational Emergence ◽  
Founding Team

Creating new ventures is one of the most central topics to entrepreneurship and is a critical step from which many theories of management, organizational behavior, and strategic management build. Therefore, this review and proposed research agenda are relevant to not only entrepreneurship scholars but also other management scholars who wish to challenge some of the implicit assumptions of their current streams of research and extend the boundaries of their current theories to earlier in the organization’s life. Given that the last systematic review of the topic was published 16 years ago, and that the topic has evolved rapidly over this time, an overview and research outlook are long overdue. From our review, we inductively generated 10 subtopics: (a) lead founder, (b) founding team, (c) social relationships, (d) cognitions, (e) emergent organizing, (f) new-venture strategy, (g) organizational emergence, (h) new-venture legitimacy, (i) founder exit, and (j) entrepreneurial environment. These subtopics are then organized into three major stages of the entrepreneurial process: co-creating, organizing, and performing. Together, the framework provides a cohesive story of the past and a road map for future research on creating new ventures, focusing on the links connecting these subtopics.

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