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1 – 10 of over 1000Philipp Loacker, Siegfried Pöchtrager, Christian Fikar and Wolfgang Grenzfurtner
The purpose of this study is to present a methodical procedure on how to prepare event logs and analyse them through process mining, statistics and visualisations. The aim is to…
Abstract
Purpose
The purpose of this study is to present a methodical procedure on how to prepare event logs and analyse them through process mining, statistics and visualisations. The aim is to derive roots and patterns of quality deviations and non-conforming finished products as well as best practice facilitating employee training in the food processing industry. Thereby, a key focus is on recognising tacit knowledge hidden in event logs to improve quality processes.
Design/methodology/approach
This study applied process mining to detect root causes of quality deviations in operational process of food production. In addition, a data-ecosystem was developed which illustrates a continuous improvement feedback loop and serves as a role model for other applications in the food processing industry. The approach was applied to a real-case study in the processed cheese industry.
Findings
The findings revealed practical and conceptional contributions which can be used to continuously improve quality management (QM) in food processing. Thereby, the developed data-ecosystem supports production and QM in the decision-making processes. The findings of the analysis are a valuable basis to enhance operational processes, aiming to prevent quality deviations and non-conforming finished products.
Originality/value
Process mining is still rarely used in the food industry. Thereby, the proposed method helps to identify tacit knowledge in the food processing industry, which was shown by the framework for the preparation of event logs and the data ecosystem.
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Rashmi Ranjan Panigrahi, Neha Singh and Kamalakanta Muduli
This paper aims to deepen the understanding of robust food supply chains (FSC) in SMEs by exploring and analyzing the literature through the lenses of digital technologies.
Abstract
Purpose
This paper aims to deepen the understanding of robust food supply chains (FSC) in SMEs by exploring and analyzing the literature through the lenses of digital technologies.
Design/methodology/approach
The study collected data from Scopus spanning from 2010 to 2024, employing selected keywords, and processed it using VOS-viewer and Biblioshiny to derive valid inferences and theoretical arguments.
Findings
The review paper identified several key themes shaping the future of supply chain management – Sustainability in SCM, Industry 4.0, Digitalization with FSCM, Circular Economy, Food Waste with Supply Chain, Food Security and Climate Change. These themes collectively bring transformative opportunities for both the adoption of digital technologies and sustainable practices in food supply chains.
Research limitations/implications
The review found limitations are rooted in financial constraints, institutional barriers and expertise-related challenges encountered within the realm of Digitalization and FSC. Government and corporate houses should focus on these limitations as well as convert them to strengthen the SMEs of FSC.
Originality/value
The study stands out as a pioneering review that not only explores Digitalization in FSC but also explores the link and evidence of SMEs in the unorganized sector, providing unique insights into a previously underexplored area.
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Richard J. Volpe, Xiaowei Cai, Presley Roldan and Alexander Stevens
The COVID-19 pandemic was a shock to the food supply chain without modern precedent. Challenges in production, manufacturing, distribution and retailing led to the highest rates…
Abstract
Purpose
The COVID-19 pandemic was a shock to the food supply chain without modern precedent. Challenges in production, manufacturing, distribution and retailing led to the highest rates of food price inflation in the US since the 1970s. The major goal of this paper is to describe statistically the impact of the pandemic of food price inflation and volatility in the US and to discuss implications for industry and for policymakers.
Design/methodology/approach
We use Bureau of Labor Statistics data to investigate food prices in the US, 2020–2021. We apply 16 statistical approaches to measure price changes and volatility and three regression approaches to measure counterfactuals of food prices, had the pandemic not occurred.
Findings
Food price inflation and volatility increased substantially during the early months of the pandemic, with a great deal of heterogeneity across food products and geographic regions. Food price inflation was most pronounced for meats, and contrary to expectations, highest in the western US Forecasting approaches demonstrate that grocery prices were about 7% higher than they would have been without the pandemic as of the end of 2021.
Originality/value
The research on COVID-19 and the food system remains in its nascent stage. As findings on food loss and waste, employment and wages, food insecurity and more proliferate, it is vital to understand how food prices were connected to these phenomena and affected. We also motivate several ideas for future work.
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Ben Arviv, Amir Shani and Yaniv Poria
The aim of the study is to capture consumers' conceptualization of ethnic food and ethnic restaurants, focusing on what it takes for ethnic restaurants to be perceived authentic.
Abstract
Purpose
The aim of the study is to capture consumers' conceptualization of ethnic food and ethnic restaurants, focusing on what it takes for ethnic restaurants to be perceived authentic.
Design/methodology/approach
Qualitative research, based on semi-structured in-depth interviews which were transcribed and subjected to inductive thematic analysis.
Findings
The findings conceptualize what ethnic food and ethnic-authentic restaurant are, leading to formulating the criteria that authentic ethnic restaurant should meet.
Research limitations/implications
Findings have practical implications for restaurateurs interested in establishing themselves as ethnically authentic and for businesses focusing on ethnic food. This study was based on Israeli-Jewish participants; studies with other populations will contribute to the findings' trustability.
Originality/value
This study provides novel and critical insights into ethnic restaurant managements and to the customer conceptualization of the concept of ethnic authentic, demonstrating it being a multifaceted concept.
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Camille Saintives and Hélène Meral
Although prior research has shown the influence of the degree of simplicity (versus complexity) in packaging design on consumer’s product and brand perceptions, no research to…
Abstract
Purpose
Although prior research has shown the influence of the degree of simplicity (versus complexity) in packaging design on consumer’s product and brand perceptions, no research to date has analyzed the effect of minimalist packaging on perceived product naturalness. This research thus aims to investigate the underlying mechanisms explaining how a minimalist food packaging design may lead consumers to perceive a product as more natural.
Design/methodology/approach
The paper is based on two pre-tests and two experiments (N = 152 and N = 220) focusing on food products. Serial–parallel mediations are performed to test the effect of minimalist packaging design on perceived product naturalness.
Findings
In a food consumption context, we demonstrate and replicate the positive impact of minimalism on perceived product uniqueness, which then positively influences both production mode and perceived taste, which, in turn, increases perceived product naturalness.
Originality/value
The findings provide new insights into the influence of food packaging design on consumers’ product perception. This paper offers a deeper understanding of the relationship between minimalist food packaging design and product naturalness by highlighting the mediating roles of perceived uniqueness, production mode and perceived taste.
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V V Ravi Kumar and Vimal Bhatt
The research methodology used for this case study follows a comprehensive approach, combining both primary and secondary sources to ensure a well-rounded understanding of the…
Abstract
Research methodology
The research methodology used for this case study follows a comprehensive approach, combining both primary and secondary sources to ensure a well-rounded understanding of the subject. Primary sources include in-depth interviews with the founders of the company, providing valuable firsthand insights into their experiences and decision-making processes. Multiple company visits were also conducted, enabling a closer examination of the operational aspects and allowing for a more holistic perspective on the case. Complementing these primary sources, secondary sources were used, consisting of a diverse array of articles from leading journals, newspapers, magazines and other reputable sources. These secondary sources offer a broader context and perspective, enriching the case study’s content and ensuring a robust foundation for classroom discussion and analysis.
Case overview/synopsis
True Elements was a clean health food brand that emerged from the vision of Mr Sreejith Moolayil and co-founder, Mr Puru Gupta, who recognized the potential of promoting healthy foods in India inspired by the health-conscious lifestyle that they observed during their work tenure in China. The co-founders began their entrepreneurial journey in 2011 with “Healthy World” kiosks inside IT company campuses in Delhi, Mumbai and Pune. However, early challenges surfaced as the target market narrowed. Undeterred, the founders sought innovative solutions to expand their reach and created “True Elements” – a brand that resonated with health-conscious consumers given its positioning as a clean and minimally processed food brand devoid of chemicals, preservatives and added sugars. True Elements excelled in the online market and catered to a few offline markets. To sustain and augment their success, the entrepreneurs sought a strategic partnership and succeeded with Marico Ltd. However, challenges remained on the horizon. One was the need to appeal to a new target group: the 25–45 age group with a lower monthly income of INR 30,000. Another pressing question was exploring the entry into the modern trade sector.
Complexity academic level
This case can be taught in undergraduate and post-graduate business management programs for marketing, strategy and innovation and entrepreneurship related courses. Apart from that, this case can also be discussed in incubator programs as cases highlighting entrepreneurship can facilitate discussions among early-stage founders, providing practical insights and lessons for their ventures. This case also can be discussed very effectively in management classes for working executives.
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Nadine Arnold and Fabien Foureault
Status distinctions matter among heterogeneous organizations within a socio-environmental field. This is exemplified in the food waste field, where six types of organizations…
Abstract
Status distinctions matter among heterogeneous organizations within a socio-environmental field. This is exemplified in the food waste field, where six types of organizations employ different excess strategies to address the issue. Theoretically, we propose that status is constructed internally through advice relationships and externally through evaluations. We posit that organizations conducting evaluations and advocating legitimate principles based on expertise (i.e., Others) are status winners. Our mixed-method study confirms that Others hold privileged positions and identifies status inconsistencies. By critically illuminating these status dynamics, we contribute to a better understanding of the roles of organizations and status in tackling socio-environmental issues.
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Siwei Bi, Jinkui Pi, Haohan Chen, Yannan Zhou, Ruiqi Liu, Yuanyuan Chen, Qianli Che, Wei Li, Jun Gu and Yi Zhang
Three-dimensional (3D) food printing is an innovative technology used to customize food products through the integration of digital technology and food ingredients. The purpose of…
Abstract
Purpose
Three-dimensional (3D) food printing is an innovative technology used to customize food products through the integration of digital technology and food ingredients. The purpose of this study is to assess the current state of research in the field of 3D food printing, identify trending topics and identify promising future research directions.
Design/methodology/approach
This bibliometric review systematically evaluates the field of 3D food printing using data from published literature in the Web of Science database. After reference screening, 812 articles were included in the analysis.
Findings
The result reveals that research in 3D food printing primarily focuses on the optimization and characterization of mechanical and rheological properties of food inks and that post-printing processing, such as laser treatment, has emerged recently as an important consideration in 3D food printing. However, extant works lack animal and human studies that demonstrate the functionality of 3D-printed food.
Originality/value
This sophisticated bibliometric analysis uncovered the most studied current research topics and the leading figures in the area of 3D food printing, providing promising future research directions.
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Olivia McDermott, Cian Moloney, John Noonan and Angelo Rosa
The current paper aims to discuss the implementation of Green Lean Six Sigma (GLSS) in the food industry to improve sustainable practices. The focus is more specifically on dairy…
Abstract
Purpose
The current paper aims to discuss the implementation of Green Lean Six Sigma (GLSS) in the food industry to improve sustainable practices. The focus is more specifically on dairy processors to ascertain the current state of the literature and aid future research direction.
Design/methodology/approach
Utilising a systematic literature review (SLR), the paper addresses various terms and different written forms in the literature. The study characterises the current deployment of GLSS in the food industry and explains the reported benefits of this approach.
Findings
GLSS, a concept that has yet to be fully explored in the food industry, as in other sectors, holds significant potential to enhance the food industry’s sustainability practices. The dairy sector, a subsector of the food industry known for its high greenhouse gas emissions, is a prime candidate for the application of GLSS. In instances where it has been applied, GLSS has demonstrated its effectiveness in improving sustainability, reducing waste, lowering greenhouse gas emissions and minimising water usage. However, the specific tools used and the model for GLSS implementation are areas that require further study, as they have the potential to revolutionise food industry operations and reduce their environmental impacts.
Practical implications
Benchmarking of this research by the food industry sector and by academics can aid understanding of the practical application of GLSS tools and aid implementation of these practices to evolve the dairy processing sector in the next decade as sustainability champions in the sector.
Originality/value
This study extensively analyses GLSS in the food industry, with a particular focus on dairy processors.
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Hati̇ce Merve Bayram and Arda Ozturkcan
This study aims to assess the effectiveness of different AI models in accurately aggregating information about the protein quality (PQ) content of food items using four artificial…
Abstract
Purpose
This study aims to assess the effectiveness of different AI models in accurately aggregating information about the protein quality (PQ) content of food items using four artificial intelligence (AI) models -– ChatGPT 3.5, ChatGPT 4, Bard AI and Bing Chat.
Design/methodology/approach
A total of 22 food items, curated from the Food and Agriculture Organisation (FAO) of the United Nations (UN) report, were input into each model. These items were characterised by their PQ content according to the Digestible Indispensable Amino Acid Score (DIAAS).
Findings
Bing Chat was the most accurate AI assistant with a mean accuracy rate of 63.6% for all analyses, followed by ChatGPT 4 with 60.6%. ChatGPT 4 (Cohen’s kappa: 0.718, p < 0.001) and ChatGPT 3.5 (Cohen’s kappa: 0.636, p: 0.002) showed substantial agreement between baseline and 2nd analysis, whereas they showed a moderate agreement between baseline and 3rd analysis (Cohen’s kappa: 0.538, p: 0.011 for ChatGPT 4 and Cohen’s kappa: 0.455, p: 0.030 for ChatGPT 3.5).
Originality/value
This study provides an initial insight into how emerging AI models assess and classify nutrient content pertinent to nutritional knowledge. Further research into the real-world implementation of AI for nutritional advice is essential as the technology develops.
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