Carlos Alberto Rojas Trejos, Jose D. Meisel and Wilson Adarme Jaimes
The purpose of this paper is to review the relevant literature in order to identify trends and suggest some possible directions for future research in the framework of…
Abstract
Purpose
The purpose of this paper is to review the relevant literature in order to identify trends and suggest some possible directions for future research in the framework of humanitarian aid distribution logistics with accessibility constraints.
Design/methodology/approach
The authors developed a systematic literature review to study the state of the art on distribution logistics considering accessibility constraints. The electronic databases used were Web of science, Scopus, Science Direct, Jstor, Emerald, EBSCO, Scielo and Redalyc. As a result, 49 articles were reviewed in detail.
Findings
This study identified some gaps, as well as some research opportunities. The main conclusions are the need for further studies on the interrelationships and hierarchies of multiple actors, explore intermodality, transshipment options and redistribution relief goods to avoid severe shortages in some nodes and excess inventory in others, studies of the vulnerability of transport networks, correlational analysis of road failures and other future lines.
Research limitations/implications
The bibliography is limited to peer-reviewed academic journals due to their academic relevance, accessibility and ease of searching. Most of the studies included in the review were conducted in high-income countries, which may limit the generalizability of the results to low-income countries. However, the authors focused on databases covering important journals on humanitarian logistics.
Originality/value
This paper contextualises and synthesises research into humanitarian aid distribution logistics with accessibility constrains, highlights key themes and suggests areas for further research.
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Keywords
Chao Miao, Ronald H. Humphrey, Shanshan Qian and In-Sue Oh
Most of the studies in entrepreneurship depend on single-source rating methods to collect data on both predictors and criteria. The threat to effect sizes as a result of using…
Abstract
Purpose
Most of the studies in entrepreneurship depend on single-source rating methods to collect data on both predictors and criteria. The threat to effect sizes as a result of using single-source ratings is particularly relevant to psychology-based entrepreneurship research. Therefore, the purpose of this paper is to explore the prospects of applying 360-degree feedback to the field of entrepreneurship and to discuss a set of cases regarding how 360-degree feedback may boost effect sizes in entrepreneurship research.
Design/methodology/approach
A qualitative review of current literature was performed.
Findings
The review indicated that the effect sizes in psychology-based entrepreneurship research are mostly small and the use of single-source ratings is prevalent; some preliminary findings supported the utility of 360-degree feedback in entrepreneurship research; entrepreneurial orientation (EO) research may benefit from 360-degree feedback; and members of top management teams, employees from research and product development, sales agents, retail buying agents, store sales clerks, and consumers are all valid informants to provide ratings of EO.
Originality/value
The present study provided theoretical explanations and used empirical evidence to elucidate how 360-degree feedback may benefit the field of entrepreneurship. In addition, recommendations for future research using 360-degree feedback in entrepreneurship research were offered and discussed. A sample research study on EO using 360-degree feedback was delineated.
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Roberto Biloslavo, David Edgar, Erhan Aydin and Cagri Bulut
This study demonstrates how artificial intelligence (AI) shapes the strategic planning process in volatile, uncertain, complex and ambiguous (VUCA) business environments. Having…
Abstract
Purpose
This study demonstrates how artificial intelligence (AI) shapes the strategic planning process in volatile, uncertain, complex and ambiguous (VUCA) business environments. Having adopted various domains of the Cynefin framework, the research explores AI's transformative potential and provide insights regarding how organisations can harness AI-driven solutions for strategic planning.
Design/methodology/approach
This conceptual paper theorises the role of AI in strategic planning process in a VUCA world by integrating extant knowledge across multiple literature streams. The “model paper” approach was adopted to provide a theoretical framework predicting relationships among considered concepts.
Findings
The paper highlights potential application of the Cynefin framework to manage complexities in strategic decision-making process, the transformative impact of AI at different stages of strategic planning, the required strategic planning characteristics within VUCA to be supported by AI and the attendant challenges posed by AI integration in the uncertain business landscape.
Originality/value
This study pioneers a theoretical exploration of AI's role in strategic planning within the VUCA business landscape, guided by the Cynefin framework. Thus, it enriches scholarly discourse and expands knowledge frontiers.
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Gopi Battineni, Nalini Chintalapudi and Francesco Amenta
After the identification of a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at Wuhan, China, a pandemic was widely spread worldwide. In Italy, about 240,000…
Abstract
Purpose
After the identification of a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at Wuhan, China, a pandemic was widely spread worldwide. In Italy, about 240,000 people were infected because of this virus including 34,721 deaths until the end of June 2020. To control this new pandemic, epidemiologists recommend the enforcement of serious mitigation measures like country lockdown, contact tracing or testing, social distancing and self-isolation.
Design/methodology/approach
This paper presents the most popular epidemic model of susceptible (S), exposed (E), infected (I) and recovered (R) collectively called SEIR to understand the virus spreading among the Italian population.
Findings
Developed SEIR model explains the infection growth across Italy and presents epidemic rates after and before country lockdown. The results demonstrated that follow-up of strict measures such that country lockdown along with high testing is making Italy practically a pandemic-free country.
Originality/value
These models largely help to estimate and understand how an infectious agent spreads in a particular country and how individual factors can affect the dynamics. Further studies like classical SEIR modeling can improve the quality of data and implementation of this modeling could represent a novelty of epidemic models.