Daniel Mahn, Antonio Lecuna, Gonzalo Chavez and Sebastian Barros
Given the importance of growth-oriented entrepreneurship in the context of economic development and the need to understand how rural communities can be developed, the purpose of…
Abstract
Purpose
Given the importance of growth-oriented entrepreneurship in the context of economic development and the need to understand how rural communities can be developed, the purpose of this research paper is to determine how the drivers of growth expectations differ between urban and rural settings.
Design/methodology/approach
The methodology is threefold: firstly, a descriptive analysis with non-parametric testing is conducted; then pooled regression model is used to analyse the predictors of growth expectations in both contexts, and finally, coarsened exact matching is used to identify possible self-selection bias.
Findings
In contrast to mainstream entrepreneurship theory, it is found that entrepreneurs’ intrinsic knowledge, skills and abilities are not significant in the rural-specific model. The only exception is entrepreneurs’ educational level, the importance of which is emphasised as a pivotal factor in increasing high-growth ventures in rural communities. Additionally, when self-selection is eliminated, rurality worsens growth intentions.
Practical implications
There is evidence that some growth-oriented entrepreneurs self-select into rural communities. Because the high-growth entrepreneurial dynamics in rural areas are unique, public policies should target purpose-driven entrepreneurial education. This includes encouraging “lifestyle entrepreneurship” (e.g. retirees returning to rural areas to become entrepreneurs), preventing entrepreneurial brain drain in rural areas and attracting highly educated urban entrepreneurs to exploit opportunities in rural areas.
Originality/value
This research attempts to contribute to the ongoing debate regarding the factors that drive high-growth entrepreneurs in rural areas by analysing rural entrepreneurs in the high-growth context of a developing economy. The focus is on Chile – a country that is rarely investigated compared to the USA or Europe – to extend the literature on high-growth ventures and entrepreneurial ecosystems.
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Keywords
Cory R.A. Hallam, Ricardo Valerdi and Carolina Contreras
The purpose of this paper is to add to the quality management body of knowledge by solidifying the connection between operational and strategic aspects of lean transformation…
Abstract
Purpose
The purpose of this paper is to add to the quality management body of knowledge by solidifying the connection between operational and strategic aspects of lean transformation. Previous research has examined these issues in isolation, demonstrating mixed results in financial and operational efficiencies. The authors show that when operational and strategic changes are jointly considered the likelihood of success for lean transformation increases.
Design/methodology/approach
The authors provide a literature review of 109 peer-reviewed papers on lean manufacturing and qualitative analysis of 23 Baldrige award winners (2000-2014) that implemented lean to assess the importance of strategic actions in achieving a sustainable competitive advantage through lean transformation.
Findings
The authors find that lean transformation yields mixed results unless strategic actions are taken by senior management. These strategic actions include but are not limited to knowledge management, human resources, and business growth and can result in performance heterogeneity by improving the output/input ratio of the firm. This performance can then manifest as either doing the same level of business with fewer resources (a profit play) or doing more business with the same resources (a growth play). As specific examples, the authors analyzed Baldrige award winners for evidence of lean strategic action to drive performance gains. The authors suggest further model validation through directed interview and/or survey research.
Originality/value
This paper clarifies the need for jointly implementing lean tools with strategic actions. The findings provide more deliberate strategic actions for organizations wishing to increase the likelihood of success of lean transformation and ultimately improve quality.
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Supply chain analytics with big data capability are now growing to the next frontier in transforming the supply chain. However, very few studies have identified its different…
Abstract
Purpose
Supply chain analytics with big data capability are now growing to the next frontier in transforming the supply chain. However, very few studies have identified its different dimensions and overall effects on supply chain performance measures and customer satisfaction. The aim of this paper to design the data-driven supply chain model to evaluate the impact on supply chain performance and customer satisfaction.
Design/methodology/approach
This research uses the resource-based view, emerging literature on big data, supply chain performance measures and customer satisfaction theory to develop the big data-driven supply chain (BDDSC) model. The model tested using questionnaire data collected from supply chain managers and supply chain analysts. To prove the research model, the study uses the structural equation modeling technique.
Findings
The results of the study identify the supply chain performance measures (integration, innovation, flexibility, efficiency, quality and market performance) and customer satisfaction (cost, flexibility, quality and delivery) positively associated with the BDDSC model.
Originality/value
This paper fills the significant gap in the BDDSC on the different dimensions of supply chain performance measures and their impacts on customer satisfaction.